PA164 Machine learning and natural language processing

Faculty of Informatics
Autumn 2005
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Lubomír Popelínský, Ph.D. (lecturer)
RNDr. Jan Blaťák, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Timetable
Wed 14:00–16:50 B410
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
Course objectives
Survey into machine learning in natural language processing. A project is as a part of this courses.
Syllabus
  • Natural language processing(NLP). Corpora. Tools for NLP.
  • Inroduction to machine learning
  • Disambiguation. Morphological disambiguaiton and word-sense disambiguation
  • Shallow parsing, syntactic analysis and learning
  • Entity recognition and collocations
  • Document categorization
  • Information extraction from text
  • Text ming
  • Web mining
  • Semantic web
Literature
  • MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
  • Learning language in logic. Edited by Sašo Džeroski - James Cussens. Berlin: Springer, 2000, x, 299. ISBN 3540411453. info
Assessment methods (in Czech)
Součástí předmětu je projekt.
Language of instruction
Czech
Teacher's information
http://www.fi.muni.cz/~popel/lectures/ll/
The course is also listed under the following terms Autumn 2003, Autumn 2004, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2005, recent)
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