Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Graduate
SUBJECT

Code	Subject	
MI070	Natural Language Processing	

Section	Semester	Hours: C+S+L	Category	Type	
Computer Science - in Romanian	7	2+0+2		optional	
Mathematics-Computer Science - in Romanian	7	2+0+2		optional	

Teaching Staff in Charge	Lect. LUPSA Dana, Ph.D., dana@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. Descriptors and FS. Variables and logic programming. Well-typed and total-well-typed feature structures. 
2. Unification grammars, definite clause grammars, PATR, HPSG grammars. Rules for rewriting. ALE as soft for HPSG grammars. 
3. Statistic methods for natural language processing. Hidden Markov Model (HMM). The probability of input sequences. Probabilistic grammars. 
4. Semantic disambiguation: algorithms for supervised, bootstrapping and non-supervised disambiguation. Application to text categorization, text summarization and machine translation.
	
Bibliography	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.MORILL:"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.E. CHARNIAK: "Statistical language learning", MIT Press, 1996.
	
Assessment	The examination is by oral exam (70%). The activity of developing a project at laboratory will be a component of the final mark (30%).