FI:PA153 NL Processing - Course Information

PA153 Natural Language Processing

Extent and Intensity

2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).

Teacher(s)

prof. PhDr. Karel Pala, CSc. (lecturer)

Guaranteed by

prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: prof. PhDr. Karel Pala, CSc.

Timetable

Wed 12:00–13:50 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

• Applied Informatics (programme FI, N-AP)
• Information Technology Security (programme FI, N-IN)
• Bioinformatics (programme FI, N-AP)
• Czech Language and Literature (programme FF, M-FI) (2)
• Czech Language and Literature (programme FF, M-HS)
• Information Systems (programme FI, N-IN)
• Informatics (programme FI, M-IN)
• Informatics (programme FI, N-IN)
• Parallel and Distributed Systems (programme FI, N-IN)
• Computer Graphics (programme FI, N-IN)
• Computer Networks and Communication (programme FI, N-IN)
• Computer Systems (programme FI, N-IN)
• Embedded Systems (eng.) (programme FI, N-IN)
• Theoretical Informatics (programme FI, N-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-TV)
• Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
• Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
• Image Processing (programme FI, N-AP)

Course objectives

The subject deals with the natural language processing on the individual language levels, particularly on the morphological, syntactic, semantic and pragmatic level. Attention is also paid to the theoretical foundations and tools used on the particular levels. Integrating the algorithms and tools into larger systems is explained as well.

Syllabus

• Levels of linguistic analysis. Representation and understanding. Language data - corpora. Types of corpora. Corpus tools. Tagging corpus texts. Disambiguation. Representation of the morphological stuctures, notation, morphological algorithms. Representation of syntactic structures - formal grammars and their types. Context-free and definite-clause grammars. Parsing algorithms. Valency frames and their types. Semantic representation. Lexical meanings (words and collocations), machine readable dictionaries, lexical databases (WordNet, EuroWordNet, thesauri). Semantic analysis of sentence meaning, Normal Translation Algorithm. Pragmatics. Discourse analysis and its segmentation. Anafora and (co-)reference. Dialogue systems. Inference and knowledge representation for NL systems. Communication agents.

Literature

• ALLEN, James. Natural language understanding. 2nd ed. Redwood City: Benjamin/Cummings Publishing Company, 1995, xv, 654 s. ISBN 0-8053-0334-0. info
• CHOMSKY, Noam. Syntaktické struktury. gramatické pravidlo. Praha: Academia, 1966, 209 s. URL info

Language of instruction

Czech

Further Comments

The course is taught annually.

• Enrolment Statistics (Autumn 2007, recent)
  
• Permalink: https://is.muni.cz/course/fi/autumn2007/PA153