"Babes-Bolyai" University of Cluj-Napoca
Faculty of Mathematics and Computer Science

Natural language processing
Code
Semes-
ter
Hours: C+S+L
Credits
Type
Section
MI282
1
2+2+0
9
compulsory
Sisteme inteligente - în limba engleză
Teaching Staff in Charge
Prof. TATAR Doina, Ph.D.,  dtatarcs.ubbcluj.ro
Aims
Natural language processing is now accepted as one of the most studied and active field of Computer Science. The notion of feature structure as linguistic object stands on the base of most recent approaches which are surveyed in this course. The optimization of the search on Web, the interfaces in natural language and the aspects of text mining are only some of motivations for studying natural language processing.
Content
1. Feature structures as objects of linguistic knowledge representation. Subsumation and unification. Proof theory of descriptors. Well-typed and total-well-typed feature structures.
2. Unification grammars. Definite clause grammars, HPSG grammars. ALE as soft for
HPSG grammars.
3. Statistics for natural language processing. Hidden Markov Model, the probability of input sequences, the most probable path. Probabilistic grammars. Text categorization.
References
1. J.ALLEN : Natural language understanding, Benjamin/Cummings Publ. , 2nd ed., 1995.
2. E. CHARNIAK: "Statistical language learning", MIT press, 1996.
3. B.CARPENTER: ALE:The attribute logic engine.User's guide. Carnegie Mellon University,1994.
4. D.JURAFSKY, J.MARTIN: Speech and language processing, Prentice Hall, 2000.
5. C.MANNING, H.SCHUTZE: Foundation of statistical natural language processing, MIT, 1999.
6. S.J.RUSSELL, P.NORVIG: Artificial intelligence.A modern approach, Prentice-Hall International,1995.
7. D.TATAR: Inteligenta artificiala: demonstrare automata de teoreme, prelucrarea limbajului natural, Editura Albastra, Microinformatica, 2001.
8. D.TATAR: Unification Grammars in Natural Language Processing, in "Recent topics in mathematical and computational linguistic, ed. C. Martin-Vide, G. Paun, Editura Academiei, 2000, pg 289-300.
9. D. TATAR: Inteligenta artificiala. Aplicatii in prelucrarea limbajului natural,Editura Albastra, Microinformatica, 2003, ISBN 973-650-100-0
Assessment
The examination is by oral exam, with the subjects from all the matter. Will be evaluated
the activity of understanding and communication of some recent papers in the field.