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E-raamat: Natural Language Processing and Computational Ling uistics 2: Semantics, Discourse and Applications: Semantics, Discourse and Applications Volume 2, Volume 2 [Wiley Online]

  • Formaat: 320 pages
  • Ilmumisaeg: 14-Nov-2017
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1119419689
  • ISBN-13: 9781119419686
  • Wiley Online
  • Hind: 174,45 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Formaat: 320 pages
  • Ilmumisaeg: 14-Nov-2017
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1119419689
  • ISBN-13: 9781119419686
Natural Language Processing (NLP) is a scientific discipline which is found at the intersection of fields such as Artificial Intelligence, Linguistics, and Cognitive Psychology. This book presents in four chapters the state of the art and fundamental concepts of key NLP areas. Are presented in the first chapter the fundamental concepts in lexical semantics, lexical databases, knowledge representation paradigms, and ontologies. The second chapter is about combinatorial and formal semantics. Discourse and text representation as well as automatic discourse segmentation and interpretation, and anaphora resolution are the subject of the third chapter. Finally, in the fourth chapter, I will cover some aspects of large scale applications of NLP such as software architecture and their relations to cognitive models of NLP as well as the evaluation paradigms of NLP software. Furthermore, I will present in this chapter the main NLP applications such as Machine Translation (MT), Information Retrieval (IR), as well as Big Data and Information Extraction such as event extraction, sentiment analysis and opinion mining.
Introduction ix
Chapter 1 The Sphere of Lexicons and Knowledge
1(74)
1.1 Lexical semantics
1(22)
1.1.1 Extension of lexical meaning
1(5)
1.1.2 Paradigmatic relations of meaning
6(10)
1.1.3 Theories of lexical meaning
16(7)
1.2 Lexical databases
23(26)
1.2.1 Standards for encoding and exchanging data
25(1)
1.2.2 Standard character encoding
25(7)
1.2.3 Content standards
32(8)
1.2.4 Writing systems
40(5)
1.2.5 A few lexical databases
45(4)
1.3 Knowledge representation and ontologies
49(26)
1.3.1 Knowledge representation
49(14)
1.3.2 Ontologies
63(12)
Chapter 2 The Sphere of Semantics
75(48)
2.1 Combinatorial semantics
75(20)
2.1.1 Interpretive semantics
75(5)
2.1.2 Generative semantics
80(2)
2.1.3 Case grammar
82(2)
2.1.4 Rastier's interpretive semantics
84(8)
2.1.5 Meaning--text theory
92(3)
2.2 Formal semantics
95(28)
2.2.1 Propositional logic
95(11)
2.2.2 First-order logic
106(7)
2.2.3 Lambda calculus
113(8)
2.2.4 Other types of logic
121(2)
Chapter 3 The Sphere of Discourse and Text
123(46)
3.1 Discourse analysis and pragmatics
123(23)
3.1.1 Fundamental concepts
123(2)
3.1.2 Utterance production
125(3)
3.1.3 Context, cotext and intertextuality
128(2)
3.1.4 Information structure in discourse
130(7)
3.1.5 Coherence
137(1)
3.1.6 Cohesion
138(4)
3.1.7 Ellipses
142(1)
3.1.8 Textual sequences
143(1)
3.1.9 Speech acts
144(2)
3.2 Computational approaches to discourse
146(23)
3.2.1 Linear segmentation of discourse
146(2)
3.2.2 Rhetorical structure theory and automatic discourse analysis
148(6)
3.2.3 Discourse interpretation: DRT
154(5)
3.2.4 Processing anaphora
159(10)
Chapter 4 The Sphere of Applications
169(90)
4.1 Software engineering for NLP software
169(22)
4.1.1 Lifecycle of an NLP software
169(1)
4.1.2 Software architecture for NLP
170(1)
4.1.3 Serial architectures
171(2)
4.1.4 Data-centered architectures
173(4)
4.1.5 Object-oriented architectures
177(1)
4.1.6 Multi-agent architectures
178(2)
4.1.7 Syntactic--semantic cooperation: from cognitive models to software architecture
180(4)
4.1.8 Programming languages for NLP
184(2)
4.1.9 Evaluation of NLP systems
186(5)
4.2 Machine translation (MT)
191(20)
4.2.1 Why is translation difficult?
192(2)
4.2.2 History of MT systems
194(2)
4.2.3 Typology of MT systems
196(2)
4.2.4 The use of MT
198(1)
4.2.5 MT techniques
199(9)
4.2.6 Example of a translation system: Verbmobil
208(3)
4.3 Information retrieval (IR)
211(23)
4.3.1 IR and related domains
211(2)
4.3.2 Lexical information and IR
213(6)
4.3.3 Information retrieval approaches
219(15)
4.4 Big Data (BD) and information extraction
234(25)
4.4.1 Structured, semi-structured and unstructured data
234(1)
4.4.2 Architectures of BD processing systems
235(2)
4.4.3 Role of NLP in BD processing
237(1)
4.4.4 Information extraction
238(21)
Conclusion 259(4)
Bibliography 263(38)
Index 301
Mohamed Zakaria Kurdi, CS Department of Lynchburg College, USA.