Course detail
Natural Language Processing
FIT-ZPJaAcad. year: 2017/2018
Foundations of the natural language processing, language data in corpora, levels of description: phonetics and phonology, morphology, syntax, semantics and pragmatics. Traditional vs. formal grammars: representation of morphological and syntactic structures, meaning representation. context-free grammars and their context-sensitive extensions, DCG (Definite Clause Grammars), CKY algorithm (Cocke-Kasami-Younger), chart-parsing. Problem of ambiguity. Electronic dictionaries: representation of lexical knowledge. Types of the machine readable dictionaries. Semantic representation of sentence meaning. The Compositionality Principle, composition of meaning. Semantic classification: valency frames, predicates, ontologies, transparent intensional logic (TIL) and its application to semantic analysis of sentences. Pragmatics: semantic and pragmatic nature of noun groups, discourse structure, deictic expressions, verbal and non-verbal contexts. Natural language understanding: semantic representation, inference and knowledge representations.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Offered to foreign students
Learning outcomes of the course unit
The students will learn to work in a team. They will also improve their programming skills and their knowledge of development tools.
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
- Realized individual project
Course curriculum
- Syllabus of lectures:
- Introduction, history of NLP, subdisciplines
- How to build a Google-like search engine, text categorization, document similarity
- Morphological analysis, inflective and derivational morphology, trie structure for dictionaries
- Syntactical analysis, constituent and dependency structures, feature structures, grammar specification formats
- Grammar formalisms, categorial grammars, LFG, HPSG, LTAG
- Methods of syntactic analysis, CKY-algorithm, chart-parsing
- Korpus linguistics, treebanks, TBL method
- Probabilistic context-free analysis, automatic alignment, machine translation
- Lexical semantics, dictionaries vs. encyclopedias, compositionality
- Transparent intensional logic for the description of meaning
- Pragmatics, contextual meaning relations, dynamic semantics
- Knowledge representation, possible-world semantics, inference
- The Semantic Web technologies, ontologies, OWL
- Individually assigned projects
Syllabus - others, projects and individual work of students:
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
- Programme IT-MSC-2 Master's
branch MBI , 0 year of study, winter semester, compulsory-optional
- Programme IT-MGR-1H Master's
branch MGH , 0 year of study, winter semester, recommended course
- Programme IT-MSC-2 Master's
branch MSK , 0 year of study, winter semester, elective
branch MMM , 0 year of study, winter semester, elective
branch MBS , 0 year of study, winter semester, elective
branch MPV , 0 year of study, winter semester, elective
branch MIS , 0 year of study, winter semester, elective
branch MIN , 0 year of study, winter semester, elective
branch MGM , 0 year of study, winter semester, elective