FPF:UIINP30 Natural Language Processing I - Course Information
UIINP30 Natural Language Processing I
Faculty of Philosophy and Science in OpavaWinter 2024
- Extent and Intensity
- 2/1/0. 4 credit(s). Type of Completion: z (credit).
- Teacher(s)
- RNDr. Miroslav Langer, Ph.D. (lecturer)
Mgr. Daniel Valenta, Ph.D. (lecturer) - Guaranteed by
- Mgr. Daniel Valenta, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava - Timetable
- Mon 8:55–10:30 B3b
- Timetable of Seminar Groups:
- 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
- Informatics B/P (programme FPF, INFOR-bpk)
- Course objectives
- In the introductory part, students get acquainted with the basic concepts of formalized natural language processing such as grammar, semantics, pragmatics, vocabulary. From the application areas, the emphasis is on the automatic text indexing and the linguistic problems involved (recognition, lemmatization and grammatical analysis of the words and multi-word terms, evaluation of semantic relations among them).
- Learning outcomes
- Students will be:
- knowledgeable in the basic terminology and formalisms
- able to define and describe basic terms such as grammar, semantics, pragmatics, vocabulary
- describe and solve the problems of morphology, homonymy, homophony, homography and further linguistic problems - Syllabus
- 1. General background and context. Lexicon, grammar, semantics (definitions of the terms and their mutual relationships).
- 2. Overview of the main application areas (automatic indexing, automatic thesaurus generation, automatic referencing, database/robot/expert system communication, etc., machine and computer-aided translation, data/knowledge bases filling, automated text correction). Connection with other computer science fields.
- 3. Linguistic problems of automatic text indexing. Recognition of the terms and determining the level of their relevance.
- 4. Solving the problem of morphology. Semantic relations among the terms and possibilities of their use. The problem of homonymy.
- 5. Automation of the creation and maintenance of the thesaurus. Thesaurus as the data structure (implementation of the thesaurus by a suitable type of the database system).
- 6. Automation of the acquisition of the relevant lexicon. Automation of finding semantic relationships among the terms.
- Literature
- required literature
- Strossa. Počítačové zpracování přirozeného jazyka. Praha, 2011. ISBN 978-80-245-1777-3. info
- recommended literature
- UHRÍN, Tibor. Přirozený jazyk a umělý jazyk. Inflow: information journal [online]. 2008, roč. 1, č. 11 [cit. 2013-04-28]. Dostupný z: http://www.inflow.cz/prirozeny-jazyk-umely-jazyk. ISSN 1802-9736
- Laboratoř zpracování přirozeného jazyka. Stručný terminologický slovník počítačové lingvistiky [online]. [cit. 2014-04-29]. Dostupné z: http://nlp.fi.muni.cz/cs/terminologie
- Teaching methods
- Interactive lecture, tutorial
- Assessment methods
- Credit:
Active participation at the tutorials min. 75%, pass the written test. - Language of instruction
- Czech
- Further Comments
- The course can also be completed outside the examination period.
- Enrolment Statistics (Winter 2024, recent)
- Permalink: https://is.slu.cz/course/fpf/winter2024/UIINP30