Introduction |
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ix | |
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Chapter 1 The Sphere of Lexicons and Knowledge |
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1 | (74) |
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1 | (22) |
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1.1.1 Extension of lexical meaning |
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1 | (5) |
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1.1.2 Paradigmatic relations of meaning |
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6 | (10) |
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1.1.3 Theories of lexical meaning |
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16 | (7) |
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23 | (26) |
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1.2.1 Standards for encoding and exchanging data |
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25 | (1) |
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1.2.2 Standard character encoding |
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25 | (7) |
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32 | (8) |
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40 | (5) |
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1.2.5 A few lexical databases |
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45 | (4) |
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1.3 Knowledge representation and ontologies |
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49 | (26) |
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1.3.1 Knowledge representation |
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49 | (14) |
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63 | (12) |
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Chapter 2 The Sphere of Semantics |
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75 | (48) |
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2.1 Combinatorial semantics |
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75 | (20) |
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2.1.1 Interpretive semantics |
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75 | (5) |
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2.1.2 Generative semantics |
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80 | (2) |
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82 | (2) |
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2.1.4 Rastier's interpretive semantics |
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84 | (8) |
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2.1.5 Meaning--text theory |
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92 | (3) |
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95 | (28) |
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2.2.1 Propositional logic |
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95 | (11) |
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106 | (7) |
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113 | (8) |
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2.2.4 Other types of logic |
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121 | (2) |
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Chapter 3 The Sphere of Discourse and Text |
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123 | (46) |
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3.1 Discourse analysis and pragmatics |
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123 | (23) |
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3.1.1 Fundamental concepts |
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123 | (2) |
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3.1.2 Utterance production |
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125 | (3) |
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3.1.3 Context, cotext and intertextuality |
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128 | (2) |
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3.1.4 Information structure in discourse |
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130 | (7) |
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137 | (1) |
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138 | (4) |
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142 | (1) |
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143 | (1) |
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144 | (2) |
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3.2 Computational approaches to discourse |
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146 | (23) |
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3.2.1 Linear segmentation of discourse |
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146 | (2) |
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3.2.2 Rhetorical structure theory and automatic discourse analysis |
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148 | (6) |
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3.2.3 Discourse interpretation: DRT |
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154 | (5) |
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3.2.4 Processing anaphora |
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159 | (10) |
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Chapter 4 The Sphere of Applications |
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169 | (90) |
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4.1 Software engineering for NLP software |
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169 | (22) |
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4.1.1 Lifecycle of an NLP software |
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169 | (1) |
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4.1.2 Software architecture for NLP |
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170 | (1) |
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4.1.3 Serial architectures |
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171 | (2) |
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4.1.4 Data-centered architectures |
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173 | (4) |
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4.1.5 Object-oriented architectures |
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177 | (1) |
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4.1.6 Multi-agent architectures |
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178 | (2) |
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4.1.7 Syntactic--semantic cooperation: from cognitive models to software architecture |
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180 | (4) |
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4.1.8 Programming languages for NLP |
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184 | (2) |
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4.1.9 Evaluation of NLP systems |
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186 | (5) |
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4.2 Machine translation (MT) |
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191 | (20) |
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4.2.1 Why is translation difficult? |
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192 | (2) |
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4.2.2 History of MT systems |
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194 | (2) |
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4.2.3 Typology of MT systems |
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196 | (2) |
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198 | (1) |
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199 | (9) |
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4.2.6 Example of a translation system: Verbmobil |
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208 | (3) |
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4.3 Information retrieval (IR) |
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211 | (23) |
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4.3.1 IR and related domains |
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211 | (2) |
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4.3.2 Lexical information and IR |
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213 | (6) |
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4.3.3 Information retrieval approaches |
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219 | (15) |
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4.4 Big Data (BD) and information extraction |
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234 | (25) |
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4.4.1 Structured, semi-structured and unstructured data |
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234 | (1) |
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4.4.2 Architectures of BD processing systems |
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235 | (2) |
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4.4.3 Role of NLP in BD processing |
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237 | (1) |
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4.4.4 Information extraction |
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238 | (21) |
Conclusion |
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259 | (4) |
Bibliography |
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263 | (38) |
Index |
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301 | |