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008			220901b |||||||| |||| 00| 0 eng d
020			_a9780195692327
020			_a0195692322
040			_cCUS
082	0	0	_a006.35 _bSID/N
100			_aSiddiqui, Tanveer _912701
245	1	0	_aNatural Language Processing and Information Retrieval
260			_aNew Delhi ; _aNew York : _bOxford Univ Press, _cc2008.
300			_aix, 406 p. : _bill. ; _c25 cm.
505			_a1. Introduction Chapter Overview 7 1.1 What is Natural Language Processing (NLP) 7 1.2 Origins of NLP 2 1.3 Language and Knowledge 3 1.4 The Challenges of NLP ^ 1.5 Language and Grammar 3 1.6 Processing Indian Languages 72 1.7 NLP Applications 13 1.8 Some Successful Early NLP Systems 75 1.9 Information Retrieval 16 2. Language Modelling Chapter Overview 27 2.1 Introduction 27 2.2 Various Grammar-based Language Models 22 2.3 Statistical Language Model 45 3. Word Level Analysis Chapter Overview 53 3.1 Introduction 53 3.2 Regular Expressions 54 3.3 Finite-State Automata 59 3.4 Morphological Parsing 63 3.5 Spelling Error Detection and Correction 77 3.6 Words and Word Classes 76 3.7 Part-of-Speech Tagging 77 4. Syntactic Analysis Chapter Overview 92 4.1 Introduction 92 4.2 Context-Free Grammar 93 4.3 Constituency 95 4.4 Parsing 104 4.5 Probabilistic Parsing 119 4.6 Indian Languages 725 5. Semantic Analysis Chapter Overview 132 5.1 Introduction 132 5.2 Meaning Representation 134 5.3 Lexical Semantics 145 5.4 Ambiguity 151 5.5 Word Sense Disambiguation 156 6. Discourse Processing Chapter Overview 7 79 6.1 Introduction 179 6.2 Cohesion 181 6.3 Reference Resolution 185 6.4 Discourse Coherence and Structure 196 7. Natural Language Generation Chapter Overview 209 7.1 Introduction 209 7.2 Architectures of NLG Systems 270 7.3 Generation Tasks and Representations 213 7.4 Applications of NLG 223 8. Machine Translation Chapter Overview 228 8.1 Introduction 228 8.2 Problems in Machine Translation 229 8.3 Characteristics of Indian Languages 230 8.4 Machine Translation Approaches 257 8.5 Direct Machine Translation 252 8.6 Rule-based Machine Translation 236 8.7 Corpus-based Machine Translation 241 8.8 Semantic or Knowledge-based MT systems 249 8.9 Translation involving Indian Languages 250 9. Information Retrieval-1 Chapter Overview 255 9.1 Introduction 255 9.2 Design Features of Information Retrieval systems 256 9.3 Information Retrieval Models 261 9.4 ClEissical Information Retrieval Models 262 9.5 Non-classical models of IR 274 9.6 Alternative Models of IR 275 9.7 Evaluation of the IR System 283 10. Information Retrieval-2 Chapter Overview 300 10.1 Introduction 300 10.2 Natural Language Processing in IR 301 10.3 Relation Matching 304 10.4 Knowledge-based Approaches 305 10.5 Conceptual Graphs in IR 307 10.6 Cross-lingual Information Retrieval 328 11. Other Applications Chapter Overview 336 11.1 Introduction 336 11.2 Information Extraction 337 11.3 Automatic Text Summarization 343 11.4 Question-Answering System 358 12. Lexical Resources Chapter Overview 371 12.1 Introduction 371 12.2 WordNet 372 12.3 FrameNet 376 12.4 Stemmers 378 12.5 Part-of-Speech Tagger 379 12.6 Research Corpora 383 12.7 Journals and Conferences in the Area 385
650		0	_aNatural language processing (Computer science) _912702
650		0	_aComputational linguistics. _912703
650		0	_aInformation retrieval. _912704
700			_912705 _aTiwary, U.S.
856			_uhttps://www.youtube.com/watch?v=X5GvBh4qY0s _yNPTEL Natural Language Processing Lecture
856			_uhttps://www.youtube.com/watch?v=n25JjoixM3I&list=PLLssT5z_DsK8BdawOVCCaTCO99Ya58ryR _yUniversity of Michigan Artificial Intelligence Lecture
942			_cL2C2 _2ddc
999			_c3382 _d3382