PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2024
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
In-person direct teaching
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (alternate examiner)
RNDr. Zuzana Nevěřilová, Ph.D. (alternate examiner)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 23. 9. to Mon 16. 12. Mon 14:00–15:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2025
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
In-person direct teaching
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (alternate examiner)
RNDr. Zuzana Nevěřilová, Ph.D. (alternate examiner)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
The course is taught each semester.
The course is taught every week.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2024
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
RNDr. Zuzana Nevěřilová, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 14:00–15:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 88 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2023
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
RNDr. Zuzana Nevěřilová, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 85 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2023
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 14. 2. to Tue 9. 5. Tue 10:00–11:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 87 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2022
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 84 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2022
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 16. 2. to Wed 11. 5. Wed 14:00–15:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 87 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2021
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 16. 9. to Thu 9. 12. Thu 14:00–15:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 83 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
English
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/en/NLPSeminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2021
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 Virtuální místnost
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 87 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2020
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 83 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2020
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 17. 2. to Fri 15. 5. Wed 10:00–11:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 87 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2019
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 B203
Prerequisites
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 83 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2019
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 12:00–13:50 B203
Prerequisites
Active presentation within the seminar program is needed. The course is especially suitable for all actively working in the Laboratory of Natural language processing, but it is open to all groups and individuals interested in any kind of text processing.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/), or other works related to text processing.
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2018
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 14:00–15:50 B203
Prerequisites
Active presentation within the seminar program is needed. The course is especially suitable for all actively working in the Laboratory of Natural language processing, but it is open to all groups and individuals interested in any kind of text processing.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/), or other works related to text processing.
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2018
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 14:00–15:50 B203
Prerequisites
Active presentation within the seminar program is needed. The course is especially suitable for all actively working in the Laboratory of Natural language processing, but it is open to all groups and individuals interested in any kind of text processing.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/), or other works related to text processing.
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2017
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 12:00–13:50 B203
Prerequisites
Active presentation within the seminar program is needed. The course is especially suitable for all actively working in the Laboratory of Natural language processing, but it is open to all groups and individuals interested in any kind of text processing.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/), or other works related to text processing.
Learning outcomes
After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem.
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Spring 2017
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Natural Language Processing Seminar

Faculty of Informatics
Autumn 2016
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 13:00–14:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2016
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 14:00–15:50 C525
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2015
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (lecturer)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2015
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 C511
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 43 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2014
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (lecturer)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 39 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2014
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
RNDr. Vojtěch Kovář, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 43 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2013
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 14:00–15:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 39 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2013
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Adam Rambousek, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 43 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2012
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 10:00–11:50 B411
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 46 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2012
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (assistant)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
RNDr. Miloš Jakubíček, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B411
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 43 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2011
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 12:00–13:50 B204
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 46 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2011
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 42 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2010
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 12:00–13:50 B203
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2010
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
prof. PhDr. Karel Pala, CSc. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 12:00–13:50 B204
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The presentations and discussion is usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2009
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B411
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 44 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • The Oxford handbook of computational linguistics. Edited by Ruslan Mitkov. Oxford: Oxford University Press, 2003, xx, 784. ISBN 0198238827. info
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
Teaching methods
Students presentations, discussion.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2009
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 B410
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
Syllabus
  • The lectures consist mostly of students' presentations. The students can control the content of the seminar in the discussions after each presentation.
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://nlp.fi.muni.cz/cs/Laboratorni_seminar
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2008
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B410
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory.
Syllabus
  • The lectures consist mostly of students' presentations. The students can control the content of the seminar in the discussions after each presentation.
Literature
  • http://nlp.fi.muni.cz/cs/Laboratorni_seminar
Assessment methods
Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Spring 2008
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 A107
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of students research (both doctoral and pregradual) in the NLP Laboratory.
Syllabus
  • The lectures consists mostly of students' presentations. The students can influence the content of the seminar in the discussions after each presentation.
Assessment methods (in Czech)
U studentů se předpokládá pravidelná účast, očekává se referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary on Natural Language Processing

Faculty of Informatics
Autumn 2007
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 10:00–11:50 B410
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly) is needed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is a presentation of results of students research (both doctoral and pregradual) in the NLP Laboratory.
Syllabus
  • The lectures consists mostly of students' presentations. The students can influence the content of the seminar in the discussions after each presentation.
Assessment methods (in Czech)
U studentů se předpokládá pravidelná účast, očekává se referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminar of Natural Language Processing Laboratory

Faculty of Informatics
Spring 2007
Extent and Intensity
0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 10:00–11:50 B411
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly) is needed.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The aim of the seminar is a presentation of results of students research (both doctoral and pregradual) in the NLP Laboratory.
Syllabus
  • The lectures consists mostly of students' presentations. The students can influence the content of the seminar in the discussions after each presentation.
Assessment methods (in Czech)
U studentů se předpokládá pravidelná účast, očekává se referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Autumn 2006, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary of Natural Language Processing Laboratory

Faculty of Informatics
Autumn 2006
Extent and Intensity
0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 10:00–11:50 B411
Prerequisites
SOUHLAS
Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly) is needed.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The aim of the seminar is a presentation of results of students research (both doctoral and pregradual) in the NLP Laboratory.
Syllabus
  • The lectures consists mostly of students' presentations. The students can influence the content of the seminar in the discussions after each presentation.
Assessment methods (in Czech)
U studentů se předpokládá pravidelná účast, očekává se referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Autumn 2005, Spring 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary of Natural Language Processing Laboratory

Faculty of Informatics
Spring 2006
Extent and Intensity
0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (assistant)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 B007
Prerequisites (in Czech)
SOUHLAS
Předpokladem pro zápis do předmětu je aktivní práce v Laboratoři a schválení přihlášky vyučujícím (P. Rychlý).
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives (in Czech)
Účelem semináře je prezentovat průběžné výsledky výzkumu v Laboratoři zpracování přirozeného jazyka, zejména práce doktorandů a studentů.
Syllabus (in Czech)
  • Seminární výuka je založená převážně na prezentacích připravených studenty. Studenti mají velký prostor ovlivnit obsah semináře v diskuzi po prezentacích.
Assessment methods (in Czech)
U studentů se minimálně předpokládá pravidelná účast, v optimálním případě se očekává referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Autumn 2005, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary of Natural Language Processing Laboratory

Faculty of Informatics
Autumn 2005
Extent and Intensity
0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 B410
Prerequisites (in Czech)
SOUHLAS
Předpokladem pro zápis do předmětu je aktivní práce v Laboratoři a schválení přihlášky vyučujícím (P. Rychlý).
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives (in Czech)
Účelem semináře je prezentovat průběžné výsledky výzkumu v Laboratoři zpracování přirozeného jazyka, zejména práce doktorandů a studentů.
Syllabus (in Czech)
  • Seminární výuka je založená převážně na prezentacích připravených studenty. Studenti mají velký prostor ovlivnit obsah semináře v diskuzi po prezentacích.
Assessment methods (in Czech)
U studentů se minimálně předpokládá pravidelná účast, v optimálním případě se očekává referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Spring 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.

PV173 Seminary of Natural Language Processing Laboratory

Faculty of Informatics
Spring 2005
Extent and Intensity
0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
doc. RNDr. Petr Sojka, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 16:00–17:50 B007
Prerequisites (in Czech)
SOUHLAS
Předpokladem pro zápis do předmětu je aktivní práce v Laboratoři a schválení přihlášky vyučujícím (P. Rychlý).
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives (in Czech)
Účelem semináře je prezentovat průběžné výsledky výzkumu v Laboratoři zpracování přirozeného jazyka, zejména práce doktorandů a studentů.
Syllabus (in Czech)
  • Seminární výuka je založená převážně na prezentacích připravených studenty. Studenti mají velký prostor ovlivnit obsah semináře v diskuzi po prezentacích.
Assessment methods (in Czech)
U studentů se minimálně předpokládá pravidelná účast, v optimálním případě se očekává referování vlastních výsledků. Studenti získávají kredity na základě prezentovaných výsledků.
Language of instruction
Czech
Further Comments
The course is taught each semester.
Teacher's information
http://www.fi.muni.cz/nlp/
The course is also listed under the following terms Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.