FPF: UBKKBP2022 Natural Language Processing I (Winter 2023)
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
Teaching methods
Interactive lecture, tutorial
Assessment methods
Credit:
Active participation at the tutorials min. 75%, pass the written test.
Course syllabus
FPF: UIIABP0023 Natural Language Processing I (Winter 2023)
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
Teaching methods
Interactive lecture, tutorial
Assessment methods
Credit:
Active participation at the tutorials min. 75%, pass the written test.
Course syllabus
FPF: UIINP30 Natural Language Processing I (Winter 2023)
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
Teaching methods
Interactive lecture, tutorial
Assessment methods
Credit:
Active participation at the tutorials min. 75%, pass the written test.
Course syllabus
FPF: UIN2022 Natural Language Processing I (Winter 2023)
Course objectives
In the introductory part, the students get acquainted with the basic concepts of the formalized NLP, such as grammar, semantics, pragmatics, vocabulary. As for the application domains, the preferred topics is automatic text indexing and the linguistic problems included (detection, lemmatization and grammatical analysis of words and multi-word expressions, evaluation of sematic relations between them).
Teaching methods
Interactive lecture
Lecture with a video analysis
Assessment methods
Credit
Course syllabus
FPF: UIINK30 Natural Language Processing I (Winter 2023)
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
Teaching methods
Interactive lectures, Lectures with discussion
Assessment methods
Credit:
Pass the written test.
Course syllabus
FPF: UBKKBK0049 Natural Language Processing I (Winter 2023)
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
Teaching methods
Interactive lecture, tutorial
Assessment methods
Credit:
Active participation at the tutorials min. 75%, pass the written test.
Course syllabus
FPF: UINK222 Natural Language Processing I (Winter 2023)
Course objectives
In the introductory part, the students get acquainted with the basic concepts of the formalized NLP, such as grammar, semantics, pragmatics, vocabulary. As for the application domains, the preferred topics is automatic text indexing and the linguistic problems included (detection, lemmatization and grammatical analysis of words and multi-word expressions, evaluation of sematic relations between them).
Teaching methods
Interactive lecture
Lecture with a video analysis
Assessment methods
Credit
Course syllabus
