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McDonald D.D., Bolc L. — Natural language generation systems
Îáñóäèòå êíèãó íà íàó÷íîì ôîðóìå Íàøëè îïå÷àòêó?
Íàçâàíèå: Natural language generation systemsÀâòîðû: McDonald D.D., Bolc L. Àííîòàöèÿ: The purpose of this collection has been to give its authors an opportunity to present their work at much greater length than is available in the usual conference paper or journal article, As a result, these papers contain details of grammatical treatments and processing details seldom seen outside of book length monographs, Their topics range from discourse theory, through mechanical translation, to deliberate writing and revision,. The authors are also wide ranging internationally, with contributions from Japan, West Germany, and Austria as well as the United States.
ßçûê: Ðóáðèêà: Computer science /Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö ed2k: ed2k stats Ãîä èçäàíèÿ: 1988Êîëè÷åñòâî ñòðàíèö: 388Äîáàâëåíà â êàòàëîã: 08.12.2005Îïåðàöèè: Ïîëîæèòü íà ïîëêó |
Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
Ïðåäìåòíûé óêàçàòåëü
Ana Stock Report Generation System, analysis of fluency skills and defects 297—305 Ana Stock Report Generation System, appendix: sample Wall Street Journal stock report 306—308 Ana Stock Report Generation System, sample output 284—286 Ana Stock Report Generation System, system architecture 281—284 Artificial intelligence research, creativity in 2 3 45 Artificial intelligence research, fluid versus essential domains in 13 14 Artificial intelligence research, human language behavior and 64 94 95 Artificial intelligence research, human-modeling in 2 3 45 Artificial intelligence research, judgment in 2 3 45 Artificial intelligence research, knowledge representation in 2 3 45 Artificial intelligence research, language understanding in 2 3 45 Artificial intelligence research, natural language interaction with computer systems and 99 100 Artificial intelligence research, problem-solving in 2 3 45 Artificial intelligence research, sensitivity in 2 3 45 Artificial intelligence research, world-modeling in 2 3 45 Computer writing, Yh program for 9—45 Computers, writing and 2 3 45 Conceptual representation in Japanese 256—278 Conceptual representation, Conceptual Dependency (CD) theory and 256 257 261 Conceptual representation, Memory Organization Packets (MOPs) and 256 261—267 277 Conceptual representation, PHRED and 312 Deliberate writing 1—45 Discrimination nets (DNs), VIE-GEN and 166 171—175 202 Fluency in natural language reports 280—308 Fluency, analysis of skills and defects in 297—305 Fluency, written texts and nature of 280 281 Formative information, Becker's phrasal lexicon in 362—364 378 379 Formative information, rules of grammar in 357—362 378 Generating Japanese text from conceptual representation 256—278 Generating language with a phrasal lexicon 353—384 Generation of sentences from a syntactic deep structure with a semantic component 205—254 Generator program, formative information in 357 Generator program, tasks of 353—357 378 German, system for surface transmissions (SUTRA) in 98—162 HAM-ANS system, implementation and integration of SUTRA in 98 100 145—153 Images, writing with vivid and continuous 1 2 45 Integrated-knowledge situation-dependent grammar principle, knowledge-based report generation and 286 291—297 305 Interface to a natural language generation system 106—113 Intermediate structure (IMS), VIE-GEN and 166 167 170 175 178—187 202 Japanese language, structure of 257—259 Japanese, generation of embedded Japanese texts 271—277 Japanese, generation of Japanese sentences 262—271 KAMP system, example of planning referring expressions 87—93 KAMP system, overview of 78—81 KAMP system, planning concept activation actions 81—83 KAMP system, satisfying multiple goals in a referring expression 86 87 KAMP system, theory of concept activation with 83—86 Knowledge-based report generation principles, integrated-knowledge situation-dependent grammar principle 286 291—297 305 Knowledge-based report generation principles, knowledge-engineering principle 286—288 Knowledge-based report generation principles, macro-level knowledge processing principle 286 289—291 Knowledge-engineering principle, knowledge-based report generation and 286—288 Language generation with PHRED, fetching 319—322 326—338 Language generation with PHRED, interpretation 319 324—326 327—339 Language generation with PHRED, restriction 319 322—324 327—338 Macro-level knowledge processing principle, knowledge-based report generation and 286 289—291 MORSYN, morphological synthesis in SUSY 253 Natural language generation system, interface to 106—113 Natural language reports, fluency in 280—308 Object-language, know and intend in 74—78 Object-oriented programming, intelligence and communication in 16—18 Pattern-concept pairs, knowledge base of PHRED 312 313 315—344 PAULINE'S specialists in 371—377 PAULINE, expansion cycle in 377 378 PAULINE, phrasal grammar in 371—377 PAULINE, syntax specialist in 364—371 Phrasal grammar, expansion cycle in 377 378 Phrasal lexicon, Becker's 362—364 378 379 Phrasal lexicon, language generation with 353—384 PHRED, comparison with other research 340—344 PHRED, detailed example of generation in 326—339 PHRED, future directions for 347—349 PHRED, generation process 319—326 PHRED, generator for natural language interfaces 312—352 PHRED, knowledge base of 315—319 PHRED, other generation systems and 344—347 PHRED, overview 313—315 Planning natural-language referring expressions, artificial intelligence research and 69—95 Planning natural-language referring expressions, English referring expressions 72—74 95 Planning natural-language referring expressions, example of 87—93 Planning natural-language referring expressions, KAMP system and 71—95 Planning natural-language referring expressions, reasoning about intention in 77 78 Planning natural-language referring expressions, reasoning about mutual knowledge in 76 77 Planning natural-language referring expressions, reference and concept activation in 75 76 94 95 Planning natural-language referring expressions, theory of reference planning in 74 75 94 95 Programs, Ana Stock Report Generation System 281—308 Programs, artificial intelligence programs and algorithmic versus behavioral 12 13 Programs, intelligence and communication in object-oriented 16—18 Programs, KAMP system 71—95 Programs, PAULINE 364—371 Programs, PHRAN 312—352 Programs, PHRED 312—352 Programs, RST system 48 53—64 Programs, SUSY 205—254 Programs, SUTRA 98—162 Programs, TEXT system 48—52 Programs, VIE-GEN 166—202 RST system, construction in 64—66 RST system, major differences between TEXT system and 66 RST system, structure description of 48 53—64 SEMNET, semantic network in VIE-LANG 166—175 SEMSYN, semantic synthesis in SUSY 231—239 Surface transformations in a natural language generation system, appendix 153—162 Surface transformations in a natural language generation system, conception of SUTRA as a component of natural language generation systems 101 102 Surface transformations in a natural language generation system, separate components for 101 SUSY machine translation system, generation component of 205—254 SUSY, (sub)processes of 153—162 SUSY, characteristics of 205—210 SUSY, extensions to the system 253 254 SUSY, generation in AI and MT 212 SUSY, morphological synthesis (MORSYN) in 253 SUSY, semantic synthesis (SEMSYN) in 231—239 SUSY, semantic vs. syntactic representation in 216—231 SUSY, syntactic deep structure with a semantic component in 213—215 SUSY, syntactic generation (SYNSYN) in 240—252 SUTRA, function and design of 102—106 SUTRA, implementation and integration with HAM-ANS system 98 100 145—162 SUTRA, knowledge sources required for 114—119 SUTRA, limitations and prospects for further development 139—145 SUTRA, transformation of the verbalized structure 119—139 SYNSYN, syntactic generation in SUSY 240—252 Syntactico-semantic lexicon (SSL), VIE-LANG and 166 169—174 200 202 Syntax specialists, PAULINE 364—371 Syntax specialists, relations among elements of the lexicon 369—371 Syntax specialists, specialists and phrase structure symbols 367—369 Text generation, overview of 47 48 Text generation, problem of text structure 47—66 TEXT system, construction in 64—66 TEXT system, defined objects in 49—52 TEXT system, major differences between RST and 66 TEXT system, operating environment of 49 TEXT system, structure description of 48—52 Transformations, application in SUTRA 119—139 VIE-GEN and 187—198 201 202 VIE-GEN, appendix of abbreviations used in 202 VIE-GEN, discrimination nets (DNs) in 166 171—175 202 VIE-GEN, generator for German texts 166—202 VIE-GEN, intermediate structure (IMS) 166 167 170 175 178—187 202 VIE-GEN, overview of 166 167 VIE-GEN, transformations in 187—198 201 202 VIE-GEN, verbalization phrase in 170—178 VIE-LANG, embedding system 167 168 VIE-LANG, syntactico-semantic lexicon (SSL) in 166 169—174 200 202 Writing, computers and 2 3 45 Writing, deliberate 1—45 Writing, non-fiction, aspects of good 3 4 Writing, non-fiction, common errors in 6—8 Writing, non-fiction, language of good 5 6 Writing, non-fiction, pragmatics of good 4 5 Writing, non-fiction, writing well in 8 9 Writing, vivid and continuous images in 1 2 45 Yh program, computer writing with 9—45 Yh program, design philosophy of 10—27 Yh program, examples of writing 27—44 Yh program, overview of the system 18—25 Yh program, writing process 25—27
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