080230061 Natural Language Processing CSE 8th Semester Anna University Coimbatore Syllabus Regulation 2008

Anna university Coimbatore Syllabus

080230061 Natural Language Processing CSE 8th Semester Anna University Coimbatore Syllabus Regulation 2008

Department of Computer science and Engineering 

Meant for Anna University Coimbatore

Syllabus 

(Regulation 2008/2010)

___________________________________________________________________________________

Details:

University:Anna University

Year: Fourth  Year

Department: B.E Computer Science and Engineering 

Semester:  (VIII) 

Content: 080230061 Natural Language Processing CSE 8th Semester Anna University Coimbatore Syllabus Regulation 2008

Subject code: 080230061

Subject Name: Natural Language Processing

Regulation: 2008 or 2010 

Post Type: Syllabus

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UNIT I            INTRODUCTION                                                                                         6

Introduction: Knowledge in speech and language processing – Ambiguity – Models and Algorithms – Language, Thought and Understanding. Regular Expressions and automata:  Regular expressions – Finite-State automata. Morphology and Finite-State Transducers: Survey of  English morphology –  Finite-State Morphological parsing – Combining FST lexicon and rules – Lexicon-Free FSTs: The porter stammer – Human morphological processing

UNIT II                       SYNTAX                                                                                           10

Word classes and part-of-speech tagging: English word classes – Tagsets for English – Part-of-speech  tagging  –  Rule-based  part-of-speech  tagging  –  Stochastic  part-of- speech   tagging           –                Transformation-based                         tagging   –    Other   issues.   Context-Free Grammars for English: Constituency – Context-Free rules and trees – Sentence-level constructions – The noun phrase – Coordination – Agreement – The verb phase and sub categorization – Auxiliaries – Spoken language syntax – Grammars equivalence and normal form – Finite-State and Context-Free grammars – Grammars and human processing. Parsing with Context-Free Grammars: Parsing as search – A Basic Top- Down parser – Problems with the basic Top-Down parser – The early algorithm – Finite- State parsing methods.

UNIT III  

 ADVANCED FEATURES AND SYNTAX                                               11

Features and Unification: Feature structures – Unification of feature structures – Features structures in the grammar – Implementing unification – Parsing with unification constraints – Types and Inheritance. Lexicalized and Probabilistic Parsing: Probabilistic context-free grammar – problems with PCFGs – Probabilistic lexicalized CFGs – Dependency Grammars – Human parsing.

UNIT IV

          SEMANTIC                                                                                                   10

Representing Meaning: Computational desiderata for representations – Meaning structure of language – First order predicate calculus – Some linguistically relevant concepts – Related representational approaches – Alternative approaches to meaning. Semantic Analysis: Syntax-Driven semantic analysis – Attachments for a fragment of English        –             Integrating  semantic analysis                 into                     the              early         parser        –          Idioms   and compositionality – Robust semantic analysis. Lexical semantics: relational among lexemes and their senses – WordNet: A database of lexical relations – The Internal structure of words – Creativity and the lexicon.

UNIT V  

                     APPLICATIONS                                                                               8

Word Sense Disambiguation and Information Retrieval: Selectional restriction-based disambiguation – Robust word sense disambiguation – Information retrieval – other information  retrieval  tasks.  Natural  Language  Generation: Introduction  to  language generation – Architecture for generation – Surface realization – Discourse planning – Other issues. Machine Translation: Language similarities and differences – The transfer

metaphor – The interlingua idea: Using meaning – Direct translation – Using statistical techniques – Usability and system development.

TOTAL : 45

TEXT BOOKS

1.  Daniel  Jurafsky  &  James  H.Martin,  “  Speech  and  Language  Processing”, Pearson Education (Singapore) Pte. Ltd., 2002.

2.  James Allen, “Natural Language Understanding”, Pearson Education, 2003.

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