UIINK30 Natural Language Processing I

Faculty of Philosophy and Science in Opava
Winter 2020
Extent and Intensity
8/0/0. 4 credit(s). Type of Completion: z (credit).
Teacher(s)
RNDr. Miroslav Langer, Ph.D. (lecturer)
Guaranteed by
RNDr. Miroslav Langer, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Prerequisites (in Czech)
TYP_STUDIA(B)
Course Enrolment Limitations
The course is offered to students of any study field.
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 lectures, Lectures with discussion
Assessment methods
Credit:
Pass the written test.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Information on the extent and intensity of the course: Přednáška 8 HOD/SEM.
The course is also listed under the following terms Winter 2019, Winter 2021, Winter 2022, Winter 2023, Winter 2024.
  • Enrolment Statistics (Winter 2020, recent)
  • Permalink: https://is.slu.cz/course/fpf/winter2020/UIINK30