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Machine translation : theoretical and methodological issues

Machine translation : theoretical and methodological issues (2회 대출)

자료유형
단행본
개인저자
Nirenburg, Sergei.
서명 / 저자사항
Machine translation : theoretical and methodological issues / edited by Sergei Nirenburg.
발행사항
Cambridge [Cambridgeshire] ;   New York :   Cambridge University Press,   c1987.  
형태사항
xv, 350 p. : ill. ; 23 cm.
총서사항
Studies in natural language processing.
ISBN
0521331250 0521336961 (pbk.)
일반주기
Includes index.  
서지주기
Bibliography: p. 317-337.
일반주제명
Machine translating.
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020 ▼a 0521331250
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040 ▼a DLC ▼c DLC ▼d m/c
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050 0 ▼a P308 ▼b .M34 1987
082 0 0 ▼a 418/.02/028 ▼2 19
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245 0 0 ▼a Machine translation : ▼b theoretical and methodological issues / ▼c edited by Sergei Nirenburg.
260 ▼a Cambridge [Cambridgeshire] ; ▼a New York : ▼b Cambridge University Press, ▼c c1987.
300 ▼a xv, 350 p. : ▼b ill. ; ▼c 23 cm.
440 0 ▼a Studies in natural language processing.
500 ▼a Includes index.
504 ▼a Bibliography: p. 317-337.
650 0 ▼a Machine translating.
700 1 0 ▼a Nirenburg, Sergei. ▼w cn.

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 418.02028 N721m 등록번호 421038081 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차


CONTENTS
Contributors = xii
Preface = xiii
1. Knowledge and choices in machine translation / SERGEI NIRENBURG = 1
 1.1. Knowledge in MT = 2
 1.2. The choices = 11
  1.2.1. Restricting the ambiguity ofsL text = 12
  1.2.2. Partial automation of translation = 12
 1.3. About this book = 15
2. Current strategies in machine translation research and development / ALLEN B. TUCKER = 22
 2.1. Introduction = 22
  2.1.1. The direct MT strategy = 22
  2.1.2. The transfer MT strategy = 23
  2.1.3. The interlingua MT strategy = 24
  2.1.4. Grammars and parsing = 26
  2.1.5. Sublanguages = 28
  2.1.6. Performance and evaluation = 28
 2.2. Operational machine translation systems = 29
  2.2.1. Georgetown and its derivatives = 29
  2.2.2. TAUM METEO = 30
  2.2.3. METAL = 31
 2.3. Experimental machine translation projects = 33
  2.3.1. EUROTRA = 33
  2.3.2. The Japanese government's MT project = 34
  2.3.3. SUSY = 36
  2.3.4. DLT = 36
  2.3.5. TRANSLATOR = 38
 2.4. Conclusions = 40
3. Linguistics and natural language processing / VICTOR RASKIN = 42
 3.1. Introduction = 42
 3.2. Why should linguistics be applied to NLP? = 42
 3.3. How not to apply linguistics to NLP = 49
 3.4. Sublanguage = 53
 3.5. Linguistics and MT = 55
4. The significance of sublanguage for automatic translation / RICHARD I. KITTREDGE = 59
 4.1. Introduction = 59
 4.2. What is sublanguage? = 59
  4.2.1. Two definitions = 59
 4.3. Sublanguages in the real world = 60
  4.3.1. Weather bulletins = 60
   4.3.2. Market reports = 61
  4.3.3. Aircraft maintenance manuals = 62
 4.4. Why is sublanguage important for automatic translation? = 62
 4.5. The importance of sublanguage grammar during analysis = 63
 4.6. Help from sublanguage grammar during lexical translation and structural transfer = 64
 4.7. Preparation for sublanguage-based automatic translation = 64
  4.7.1. Comparing candidate sublanguages = 64
 4.8. Estimating computational traciability = 66
5. Knowledge-based machine translation, the CMU approach / JAIME G. CARBONELL ; MASARU TOMITA = 68
 5.1. Approaches to machine translation = 68
  5.1.1. A historical perspective = 68
  5.1.2. Existing approaches = 69
   5.1.2.1. Translation aids = 70
   5.1.2.2. The post-editing approach = 71
   5.1.2.3. The pre-editing approach = 72
  5.1.3. The knowledge-based approach = 74
  5.1.4. The interactive approach = 76
   5.1.4.1. Interactive sentence disambiguation = 77
   5.1.4.2. Bypassing source text = 78
  5.1.5. Concluding remarks = 80
 5.2. Efficient knowledge-based translation = 81
  5.2.1. The new generation MT systems at CMU = 81
  5.2.2. System overview = 83
  5.2.3. Entity-oriented grammar formalism = 83
  5.2.4. Functional grammar formalism = 86
  5.2.5. Grammar precompilation and efficient on-line parsing = 87
  5.2.6. Long-term technological directions = 89
6. The structure of interlingua in TRANSLATOR / SERGEI NIRENBURG ; VICTOR RASKIN ; ALLEN B. TUCKER = 90
 6.1. Delimiting the problem = 90
 6.2. Configuration of TRANSLATOR = 90
 6.3. DRL = 92
  6.3.1. Frames = 95
  6.3.2. Properties = 97
  6.3.3. From the root to a leaf = 97
 6.4. GRL = 98
  6.4.1. Text = 99
  6.4.2. Sentence = 99
  6.4.3. Clause = 100
  6.4.4. Process = 100
  6.4.5. State = 101
  6.4.6. Object = 101
  6.4.7. Time = 101
  6.4.8. Space = 102
  6.4.9. Slot operators = 102
  6.4.10. Modality = 102
  6.4.11. Focus = 102
  6.4.12. Discourse structure = 103
  6.4.13. Speech act = 103
  6.4.14. Other slots and slot fillers = 104
 6.5. Knowledge about SL = 104
 6.6. A sample analysis = 105
 6.7. Conclusion = 111
7. Basic theory and methodology in EUROTRA / DOUG ARNOLD ; LOUIS des TOMBE = 114
 7.1. Introduction = 114
 7.2. Methodology and basic ideas = 116
 7.3. The ,T notation = 120
  7.3.1. Generative devices: Gs = 120
  7.3.2. Translators: Ts = 122
 7.4. Contents of linguistic representation levels = 126
  7.4.1. Overview = 126
  7.4.2. An example = 128
 7.5. Work in progress = 134
8. Machine translation as an expert task / RODERICK L. JOHNSON ; PETER WHITELOCK = 136
 8.1. Introduction = 136
 8.2. MT as simulation of translator behavior = 136
 8.3. Knowledge in translation = 137
 8.4. A model of translation 13 = 8
 8.5. The division of tabor in MT = 140
  8.5.1. After-postediting = 140
  8.5.2. During-interactive MT = 140
  8.5.3. Before-pre-editing = 141
 8.6. Distribution of knowledge in human and machine translation = 141
 8.7. Towards more productive interaction strategies = 142
9. On human-machine interaction in translation / ALAN MELBY = 145
 9.1. Types of translation = 145
 9.2. Types of human interaction = 146
 9.3. Types ofMT = 147
 9.4. Factors in interaction = 148
 9.5. A particular translator work station = 148
 9.6. Level one = 149
 9.7. Level two = 150
 9.8. Level three = 150
 9.9. Conclusion = 151
10. Reflections on the knowledge needed to process ill-formed language / RALPH M. WEISCHEDEL ; LANCE A. RAMSHAW = 155
 10.1. Introduction = 155
 10.2. Ill-formedness and applications = 157
 10.3. Morphology and phonetics = 157
 10.4. Role of syntax = 158
 10.5. Semantic knowledge = 159
 10.6. Prospects from pragmatics = 161
  10.6.1. The search space = 162
  10.6.2. An example = 163
  10.6.3. Other types of text = 165
 10.7. Combining knowledge sources = 165
 10.8. Conclusions = 167
11. An integrated theory of discourse analysis / JAMES PUSTEJOVSKY = 168
 11.1. Approaches to discourse analysis = 168
  11.1.1. Setting the stage = 168
  11.1.2. Structural analysis = 171
  11.1.3. Goal recognition = 173
  11.1.4. Model theory = 176
 11.2. Shortcomings of the current approaches to discourse analysis = 177
  11.2.1. Conversational moves versus coherence = 177
 11.3. Levels of discourse analysis = 180
 11.4. CICERO: inference controlling for discourse analysis = 187
  11.4.1. A natural language interface for a case-based legal reasoning system = 187
 11.5. Managing the discourse = 188
 11.6. Conclusion = 191
12. Natural language generation: complexities and techniques / DAVID D. MCDONALD = 192
 12.1. Introduction = 193
 12.2. Generation versus comprehension = 193
 12.3. Terminology = 195
 12.4. Why does generation seem to be a simple process? = 197
 12.5. The direct replacement technique = 200
 12.6. Modern approaches to generation = 204
 12.7. Mixing control with the statement of the grammar = 206
  12.7.1. Augmented transition networks in generation = 206
   12.7.2. Systemic grammars = 208
 12.8. Stating the constraints of the grammar independently = 210
 12.9. Functional unification grammars = 211
 12.10. Multi-level, description-directed generation = 214
 12.11. Relating modern generation approaches to MT = 224
13. The research environment in the METAL project / JOHN S. WHITE = 225
 13.1. Introduction = 225
 13.2. History of development = 225
  13.2.1. Grammar-software distinction = 226
  13.2.2. Parser studies = 226
  13.2.3. METAL In a standalone environment = 227
 13.3. The METAL system = 227
 13.4. METAL software development tools = 229
 13.5. Grammar development tools = 229
  13.5.1. TRANSLATE-SENTENCE = 230
  13.5.2. PTREE = 231
  13.5.3. DRAW-TREES = 234
  13.5.4. Grammar-rule access devices = 234
   13.5.4.1. PGR ('print German rule') = 234
   13.5.4.2. EGR ('edit German rule') = 235
   13.5.4.3. DGR ('delete German rule') = 238
  13.5.5. TRACE-SYNTAX = 238
  13.5.6. ENGLISH n = 239
 13.6. Text translation tools = 240
 13.7. Lexicon development tools = 241
  13.7.1. INTERCODER = 241
  13.7.2. Development lexical functions = 242
   13.7.2.1. VALIDATOR = 242
   13.7.2.2. PREANALYZER = 244
   13.7.2.3. DEFAULTER = 244
   13.7.2.4. CHECK-LEXECAL-CONSISTENCY = 244
   13.7.2.5. PGW ('print German word') = 245
   13.7.2.6. EGW ('edit German word') = 246
   13.7.2.7. DGW ('delete German word') = 246
 13.8. Conclusion = 246
14. Knowledge resource tools for accessing large text files / DONALD E. WALKER = 247
 14.1. Introduction = 247
 14.2. Sources = 248
 14.3. Resources = 249
 14.4. FORCE4, a system for full-text content assessment = 251
 14.5. How FORCE4 processes text = 251
  14.5.1. A discussion of the FORCE4 approach = 253
 14.6. THOTH, a system for concept elaboration = 257
 14.7. Discussion = 259
15. Role of structural transformation in a Machine translation system / MAKOTO NAGAO = 262
 15.1. Necessity of structural transformation = 262
 15.2. General principles of our machine translation system = 263
 15.3. Structural transformation at the transfer stage = 265
  15.3.1. Structural transformation at pre-transfer loop = 265
 15.4. Word selection and structural transformation at transfer stage = 268
 15.5. Structural transformation at generation stage = 271
 15.6. Conclusion = 275
 15.7. Appendix = 275
16. An experiment in lexicon-driven machine translation / RICHARD E. CULLINGFORD ; BOYAN A. ONYSHKEVYCH = 278
 16.1. Introduction: lexicon-driven machine translation = 278
 16.2. Goals and methodology = 279
 16.3. A lexicon-directed analyzer = 283
  16.3.1. Analyzing English = 284
  16.3.2. Analyzing U krainian = 286
  16.3.3. Pronominal reference = 289
  16.3.4. Prepositional constructions = 290
  16.3.5. Word meaning disambiguation = 291
  16.3.6. Surface-semantic machine translation = 293
  16.3.7. Surface-semantic generation = 293
  16.3.8. Dictionary entries for English = 295
  16.3.9. Annotating surface-semantic forms for output = 299
  16.3.10. Distributed target realization = 299
 16.4. Conclusions = 301
17. Integrating syntax and semantics / STEVEN L. LYTINEN = 302
 17.1. Introduction = 302
 17.2. Why syntax needs semantics = 303
 17.3. Why semantics needs syntax = 306
 17.4. A parser which satisfies both constraints = 310
 17.5. Conclusion = 315
References = 317
Subject index = 338
Author index = 346


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