UIIABP0023 Natural Language Processing I

Faculty of Philosophy and Science in Opava
Winter 2021
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)
RNDr. Miroslav Langer, Ph.D. (seminar tutor)
Guaranteed by
RNDr. Miroslav Langer, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Timetable
Mon 19:45–21:20 PED2
  • Timetable of Seminar Groups:
UIIABP0023/A: Mon 20. 9. to Wed 1. 12. Wed 17:15–18:00 PED2, M. Langer
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
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. Automatization 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. Automatization of the acquisition of the relevant lexicon. Automatization of finding semantic relationships among the terms.
Teaching methods
Interactive lecture, tutorial
Assessment methods
Credit:
Active participation at the tutorials min. 75%, pass the written test.
Language of instruction
Czech
The course is also listed under the following terms Winter 2020, Winter 2022, Winter 2023, Winter 2024.
  • Enrolment Statistics (Winter 2021, recent)
  • Permalink: https://is.slu.cz/course/fpf/winter2021/UIIABP0023