Cercone Computational Linguistics

International Series in Modern Applied Mathematics and Computer Science
1. Auflage 2014
ISBN: 978-1-4831-9061-7
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 258 Seiten, Web PDF

Computational Linguistics provides an overview of the variety of important research in computational linguistics in North America. This work is divided into 15 chapters and begins with a survey of the theoretical foundations and parsing strategies for natural language. The succeeding chapters deal with psychological and linguistic modeling, discourse processing analysis, text and content analysis, and natural language understanding, as well as knowledge organization, memory models, and learning. Other chapters describe the programming systems and considerations for computation linguistics. The last chapters look into the nature of natural language front-end processes to database systems. These chapters also examine the human factors interface. This book will prove useful to computing scientists, philosophers, psychologists, and linguists.

Autoren/Hrsg.

Cercone, Nick

Inhaltsverzeichnis

1;Front Cover;1
2;Computational Linguistics;4
3;Copyright Page;5
4;Table of Contents;8
5;PREFACE;6
6;INTRODUCTION;10
7;CHAPTER 1. INTERPRETING NETWORK
FORMALISMS;14
7.1;1. IMPRIMATUR;14
7.2;2. DOCTRINAL PREAMBLE;14
7.3;3. INTRODUCTION;14
7.4;4. SNePS;15
7.5;5. INHERITANCE;18
7.6;6. THE SEMANTICS OF INHERITANCE;19
7.7;REFERENCES;25
8;CHAPTER 2. SOME REPRESENTATIONAL ISSUES IN DEFAULT
REASONING;28
8.1;1. INTRODUCTION;28
8.2;2. INTERACTING NORMAL DEFAULTS;29
8.3;3. DEFAULT INHERITANCE IN HIERARCHIES: NETWORK REPRESENTATIONS;35
8.4;4. DISCUSSION;38
8.5;5. CONCLUSIONS;40
8.6;REFERENCES;40
9;CHAPTER 3.
GENERATING LANGUAGE FROM CONCEPTUAL GRAPHS;42
9.1;1. CONCEPTUAL GRAPHS;42
9.2;2. THE UTTERENCE PATH;43
9.3;3. AUGMENTED PHRASE STUCTURE GRAMMAR;47
9.4;4. MAPPING
GRAMM AR, RATH ER THAN GENERATIVE GRAMMAR;54
9.5;REFERENCES;55
10;CHAPTER 4. SEMANTIC PROCESSING OF TEXTS IN
RESTRICTED SUBLANGUAGES;58
10.1;1. SEMANTIC PROCESSING OF "REAL" TEXTS;58
10.2;2. THREE PRACTICAL APPLICATIONS OF SEMANTIC PROCESSING TO REAL TEXTS;59
10.3;3. SUBLANGUAGE;62
10.4;4. STOCK MARKET REPORTS;63
10.5;5. AUTOMATIC EXTRACTION OF CONTENT REPRESENTATIONS;65
10.6;6. CONCLUDING REMARKS;70
10.7;REFERENCES;71
11;CHAPTER 5. THE CONTROL OF INFERENCING IN
NATURAL LANGUAGE UNDERSTANDING;72
11.1;1. INTRODUCTION;72
11.2;2. THE CONTROL OF INFERENCING;75
11.3;3. INFERENCINGANDTEXT STRUCTURE;77
11.4;4. A DATA STRUCTURE FOR CONTEXT;78
11.5;5. THE NATURE OF THE FIT ALGORITHM;80
11.6;6. CONCLUSIONS;82
11.7;REFERENCES;83
12;CHAPTER 6. WHAT THE SPEAKER MEANS: THE RECOGNITION
OF SPEAKERS' PLANS IN DISCOURSE;84
12.1;1. INTRODUCTION;84
12.2;2. BACKGROUNDFORA
NEW MODEL;84
12.3;3. DEFINING INTENDED SPEAKER MEANING;85
12.4;4. MODEL OF RECOGNITION OF INTENDED MEANING;87
12.5;5. THE SPEAKER INTENDED THAT THE HEARER pt THAT PC(S);88
12.6;5. EXTENDING THE
MODEL;88
12.7;6. REASONING ABOUT A USER'S "BUGGY" PLANS;89
12.8;7. COMPARISON WITH AN EARLIER APPROACH;92
12.9;REFERENCES;95
13;CHAPTER 7. FORMAL SEMANTIC AND COMPUTER
TEXT PROCESSING, 1982;96
13.1;1. INTRODUCTION;96
13.2;2. TEXT AND DISCOURSE;97
13.3;3.
E-SCRIPT AND GRAMMAR;100
13.4;4. THE TRANSCRIPTIONS;103
13.5;5. DEFINITIONS OF SOME INTERESTING PROBLEMS;104
13.6;CONCLUSIONS;107
13.7;REFERENCES;107
14;CHAPTER 8. ARGOT: A SYSTEM
OVERVIEW;110
14.1;1. BACKGROUND;110
14.2;2. A SIMPLE DIALOGUE MODEL;112
14.3;3. THE ARGOT SYSTEM;113
14.4;4. COMMUNICATIVE GOAL REASONING;116
14.5;5. ISSUES IN KNOWLEDGE REPRESENTATION;117
14.6;6. CONCLUDING REMARKS;121
14.7;REFERENCES;121
15;CHAPTER 9. DESCRIPTION DIRECTED CONTROL: ITS IMPLICATIONS
FOR NATURAL LANGUAGE GENERATION;124
15.1;1. INTRODUCTION: COMPUTATIONAL HYPOTHESES IN A.I.;124
15.2;2. THE ROLE OF THE CONTROL STRUCTURE IN GENERATION;125
15.3;3. ASSUMPTIONS ABOUT THE INPUT TO THE GENERATION PROCESS;127
15.4;4. DESCRIPTION-DIRECTED CONTROL;129
15.5;5. IMPLICATIONS OF THE ALGORITHM;135
15.6;6. CONCLUSION: PROPERTIES OF THE VIRTUAL MACHINE;141
15.7;7. REFERENCES;142
16;CHAPTER 10. UNDERSTANDING NOVEL
LANGUAGE;144
16.1;1. INTRODUCTION;144
16.2;2. SCHEMA LEARNING;146
16.3;3. UNDERSTANDING METAPHOR;151
16.4;4. CONCLUSION;159
16.5;REFERENCES;159
17;CHAPTER 11. A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL
LANGUAGES;162
17.1;1. INTRODUCTION;162
17.2;1. CARDINALITY OF FUZZY SETS;167
17.3;3. FUZZY QUANTIFIERS AND CARDINALITY OF FUZZY SETS;172
17.4;4. MEANING REPRESENTATION BY TEST-SCORE SEMANTICS;183
17.5;CONCLUDING REMARK;193
17.6;REFERENCES;193
17.7;APPENDIX;195
18;CHAPTER 12. RECOGNITION MECHANISMS FOR SCHEMA-BASED
KNOWLEDGE REPRESENTATIONS;198
18.1;1. INTRODUCTION;198
18.2;2. SCHEMATA;199
18.3;3. SEARCH IN SCHEMA NETWORKS;202
18.4;4. FORMAL PARSING ALGORITHMS;204
18.5;5. RECOGNITION MECHANISMS FOR SCHEMATA;206
18.6;6. CONCLUSION;210
18.7;REFERENCES;211
19;CHAPTER 13. AN APPROACH TO THE ORGANIZATION OF KNOWLEDGE AND ITS USE IN NATURAL
LANGUAGE RECALL TASKS;214
19.1;1. INTRODUCTION;214
19.2;2. THE REPRESENTION SCHEME;215
19.3;3. USING |LISP IN A NATURAL LANGUAGE DOMAIN;218
19.4;4. THE RECALL TASK;220
19.5;5. SOME LEGAL EXAMPLES;224
19.6;6. INTELLIGENT GARBAGE COLLECTION;224
19.7;7. CONCLUSIONS;225
19.8;REFERENCES;226
20;CHAPTER 14. MINIMAL AND ALMOST MINIMAL PERFECT HASH FUNCTION SEARCH WITH APPLICATION TO
NATURAL LANGUAGE LEXICON DESIGN;228
20.1;1. INTRODUCTION;228
20.2;2. DEVELOPMENT OF THE PERFECT HASH ALGORITHMS;229
20.3;3. DESCRIPTION OF THE ALGORITHMS;233
20.4;4. PERFORMANCE OF THE ALGORITHMS;236
20.5;5. APPLICATION OF PERFECT HASH FUNCTIONS TO NATURAL LANGUAGE LEXICON DESIGN;238
20.6;6. CONCLUSIONS;240
20.7;REFERENCES;240
21;CHAPTER 15. EXTENDED NATURAL LANGUAGE
DATA BASE INTERACTIONS;246
21.1;1. INTRODUCTION;246
21.2;2. RESPONDING TO QUERIES ABOUT DATA BASE STRUCTURE;246
21.3;3. TAKING THE INITIATIVE IN RESPONDING TO QUERIES;249
21.4;4. CONCLUSION;257
21.5;REFERENCES;257
22;INDEX;258