FI:PA153 NL Processing - Course Information
PA153 Natural Language Processing
Faculty of InformaticsAutumn 2003
- 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. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: prof. PhDr. Karel Pala, CSc. - Timetable
- Tue 16:00–17:50 B410
- Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Informatics (programme FI, N-AP)
- Czech Language and Literature (programme FF, M-FI) (2)
- Czech Language and Literature (programme FF, M-HS)
- Informatics (programme FI, M-IN)
- 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, N-SS)
- 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
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
- Enrolment Statistics (Autumn 2003, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2003/PA153