"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
MI070
7
2+0+2
6
optional
Informatică
MI070
7
2+0+2
6
optional
Matematică-Informatică
Teaching Staff in Charge
Assoc.Prof. TATAR Doina, Ph.D., dtatar@cs.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. Also, are presented the semantics and pragmatics of natural language processing which are central in human -computer interaction, information retrieval, text mining, text summarization and text generation.
Content
1. Feature structures (FS) as objects of linguistic knowledge representation. Subsumation and unification of FSs. 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 procesing . Hidden Markov Model, the probability of input sequences. Probabilistic grammars. Text categorization.
4. Word disambiguation: algorithms for supervized, bootstrapping and non-supervized disambiguation. Algorithms for client/server disambiguation. Reference (anaphora) resolution. Automatic interpretation of dialogue acts. Applications to text categorization, text summarization and machine translation.
References
1. J.Allen : $Natural language understanding$, Benjamin/Cummings Publ., 2nd ed., 1995.
2. B.Carpenter: $The logic of typed feature structures$, Cambridge University Press,1992. 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. G.Morrill:$Type LogicalGrammar.Categorial Logic of Signs$, Kluwer Academic Publishers, 1994.
7. S.J.Russell, P.Norvig: $Artificial intelligence.A modern approach$, Prentice-Hall International, 1995.
8. D.Tatar: $Inteligenta artificiala: demonstrare automata de teoreme, prelucrarea limbajului natural$, Editura Albastra, Microinformatica, 2001.
9. D.Tatar: $Inteligenta artificiala. Aplicatii in prelucrarea limbajului natural$, Ed. Albastra, Microinformatica, 2003
10.http://www.scs.ubbcluj.ro/scs/cursuri/PaginaPLN/index.html
Assessment
The examination is by oral exam, with the subjects from all the matter.