FI:PA164 Learning and natural language - Course Information

PA164 Machine learning and natural language processing

Extent and Intensity

2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).

Teacher(s)

doc. RNDr. Lubomír Popelínský, Ph.D. (lecturer)
RNDr. Jan Blaťák, Ph.D. (seminar tutor)

Guaranteed by

prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics

Timetable

Tue 12:00–13:50 B410

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

there are 18 fields of study the course is directly associated with, display

Course objectives

Survey into machine learning in natural language processing. A project is as a part of this courses.

Syllabus

• Natural language processing(NLP). Corpora. Tools for NLP.
• Inroduction to machine learning
• Disambiguation. Morphological disambiguaiton and word-sense disambiguation
• Shallow parsing, syntactic analysis and learning
• Entity recognition and collocations
• Document categorization
• Information extraction from text
• Text mining
• Web mining
• Semantic web

Literature

• MANNING, Christopher D. and Hinrich SCHÜTZE. Foundations of statistical natural language processing. Cambridge: MIT Press, 1999, xxxvii, 68. ISBN 0-262-13360-1. info
• Learning language in logic. Edited by Sašo Džeroski - James Cussens. Berlin: Springer, 2000, x, 299. ISBN 3540411453. info

Assessment methods

A project is as a part of the course.

Language of instruction

Czech

Further Comments

Study Materials

Teacher's information

http://www.fi.muni.cz/~popel/lectures/ll/

• Enrolment Statistics (Autumn 2008, recent)
  
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