A computational model of metaphor interpretation:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | German |
| Veröffentlicht: |
Boston u.a.
Academic Press
1990
|
| Schriftenreihe: | Perspectives in artificial intelligence
8 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXIII, 229 S. |
| ISBN: | 0124747302 |
Internformat
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| 100 | 1 | |a Martin, James H. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a A computational model of metaphor interpretation |c James H. Martin |
| 264 | 1 | |a Boston u.a. |b Academic Press |c 1990 | |
| 300 | |a XXIII, 229 S. | ||
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| 650 | 4 | |a Métaphore - Informatique | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Metaphor |x Data processing | |
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Datensatz im Suchindex
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|---|---|
| adam_text | Titel: A computational model of metaphor interpretation
Autor: Martin, James H.
Jahr: 1990
Contents
List of Figures xiii
Acknowledgements xv
Preface: R. Wilensky xvii
Preface xxi
1 Introduction 1
1.1 Conventional Metaphor 1
1.2 The Metaphoric Knowledge Approach 2
1.3 Previous Approaches 4
1.4 Constraints from Psycholinguistics 5
1.5 Details of the Approach 6
1.5.1 Representation 7
1.5.2 Interpretation 7
1.5.3 Learning 12
1.6 Summary 21
2 Related Research 23
2.1 Knowledge-Deficient Approaches 23
2.1.1 Natural Language Processing Approaches 24
2.1.1.1 Wilks 24
2.1.1.2 Fass 26
2.1.1.3 Russell 27
2.1.2 Analogical Approaches 29
2.1.2.1 Winston and Carbonell 30
2.1.2.2 Gentner 30
2.1.2.3 Greiner and Burstein 31
2.2 Knowledge-Based Approaches 32
ix
x CONTENTS
2.3 Word Sense Acquisition 34
3 Conventional Metaphoric Knowledge 35
3.1 Introduction 35
3.2 Conventional Metaphorical Meaning 36
3.3 Extended Metaphors 37
3.3.1 Core Structures 38
3.3.2 Metaphor and Core Structures 40
3.3.3 Structure of Extended Metaphors 41
3.3.4 Representational Requirements of Extended Metaphors 45
3.4 Metaphor Hierarchies 46
3.5 Similarity Among Metaphors 47
3.6 Challenges to Metaphorical Regularity 49
3.7 Motivation 52
3.8 Summary 52
4 Knowledge Representation 55
4.1 Introduction 55
4.2 KODIAK 55
4.2.1 Structured Associations 60
4.3 Conventional Metaphorical Knowledge 61
4.4 Representing Conventional Metaphors 63
4.5 Representing Extended Metaphors 67
4.5.1 Core Structures 67
4.5.2 Metaphorical Preservation of Core Structures .... 71
4.5.3 Extended Metaphors 75
4.6 Metaphor Hierarchies 78
4.7 Metaphorical Interactions 83
4.8 Summary 87
5 Metaphoric Interpretation 89
5.1 Introduction 89
5.2 Conceptual Analysis 89
5.2.1 Initial Parse 90
5.2.2 Interpretation 91
5.3 Interpretation Algorithm 95
5.4 Summary 107
6 Overview of Metaphor Extension 109
6.1 Introduction 109
6.2 The Learning Approach 109
6.3 Context 110
CONTENTS xi
6.4 The Extension Approach Ill
6.4.1 Similarity Learning Ill
6.4.2 Core Extensions 117
6.5 The Extension Algorithm 121
6.6 Annotated Example 122
6.7 Summary 128
7 The Metaphor Extension System 131
7.1 Introduction 131
7.2 The mes Algorithm 131
7.2.1 Step 0: Initial Processing 132
7.2.2 Step 1: Characterize The New Input 133
7.2.3 Step 2: Collecting Relevant Metaphors 134
7.2.4 Step 3: Evaluating the Candidates 139
7.2.5 Step 4: Applying the Candidate Metaphor 142
7.2.6 Step 5: Storing the New Metaphor 144
7.3 Summary 145
8 Learning Using Similarity 147
8.1 Introduction 147
8.2 An Example 148
8.3 Similarity Algorithm 154
8.3.1 Step 0: Accept 155
8.3.2 Step 1: Assign Roles 158
8.3.3 Step 2: Abstraction 158
8.3.4 Step 3: Concretion 161
8.4 Degrees of Similarity 163
8.5 Summary 167
9 Learning Extended Metaphors 169
9.1 Introduction 169
9.2 Core Extension Algorithm 170
9.2.1 Direct Extension 175
9.2.1.1 Step 0: Accept 175
9.2.1.2 Step 1: Characterization 176
9.2.1.3 Step 2: Application 177
9.2.1.4 Step 3: Concretion 180
9.2.2 Realization 181
9.2.3 Intermediate Extension 184
9.3 Relation to Analogy 187
9.4 Summary 187
xii CONTENTS
10 Previous Literature Revisited 189
10.1 Introduction 189
10.2 Hobbs 190
10.3 Wilks 196
10.4 DeJong and Waltz 199
10.5 Fass 202
10.6 Russell 205
10.7 Summary 210
11 Conclusions 213
11.1 Introduction 213
11.2 Representation 213
11.3 Interpretation 214
11.3.1 Word-Senses Versus Conventional Metaphors .... 215
11.4 Learning 216
11.5 Psycholinguistic Constraints Reconsidered 217
11.6 Problems 218
Bibliography 221
Index 225
List of Figures
3.1 Core and Extended Metaphors 42
4.1 Primitives of KODIAK 56
4.2 Part-Whole Relation 57
4.3 Has-Table-Top Relation 58
4.4 Slot Notation 60
4.5 Has-Table-Top Structured Association 62
4.6 Killing 64
4.7 Terminating 65
4.8 Metaphor Maps 66
4.9 Kill-Terminate-Sense 68
4.10 Kill-Terminate-Sense 69
4.11 Giving, Getting and Having 70
4.12 Infecting 73
4.13 Giving a Disease 74
4.14 Give-A-Cold 75
4.15 Have-A-Cold 76
4.16 Having Extending to Giving 77
4.17 Metaphor-map Hierarchy 81
4.18 Multiple Inheritance 82
4.19 Giving and Selling Ideas 84
4.20 Giving Metaphors 85
5.1 Primal Representations 91
5.2 Final Concretion Step 93
5.3 Infection Concretion 93
5.4 Giving a Disease 94
6.1 Extension Inferences 112
6.2 In-Emacs Metaphor 113
6.3 Emacs-Lisp Similarity Connection 113
xiii
xiv LIST OF FIG URES
6.4 Entering Enclosed Core Connection 118
7.1 Search After Step 1 136
7.2 Search After Step 3 137
7.3 Search After Step 4 138
8.1 Give-Cold Metaphor 149
8.2 Primal Representation 149
8.3 Give-Cold Similarity Connection 150
8.4 Cold and Flu Infecting 151
8.5 Infecting 152
8.6 Primal Representation 155
8.7 Killing a conversation 156
8.8 Terminating a conversation 156
8.9 Process Conversation Connection 160
8.10 Terminating a computer-process 163
8.11 Induce an idea in a person 165
8.12 Cause-New-State Hierarchy 166
9.1 Core-Extension Inferences 173
9.2 Giving and Having a Disease 177
9.3 Infection 179
|
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| institution | BVB |
| isbn | 0124747302 |
| language | German |
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| physical | XXIII, 229 S. |
| publishDate | 1990 |
| publishDateSearch | 1990 |
| publishDateSort | 1990 |
| publisher | Academic Press |
| record_format | marc |
| series | Perspectives in artificial intelligence |
| series2 | Perspectives in artificial intelligence |
| spelling | Martin, James H. Verfasser aut A computational model of metaphor interpretation James H. Martin Boston u.a. Academic Press 1990 XXIII, 229 S. txt rdacontent n rdamedia nc rdacarrier Perspectives in artificial intelligence 8 Métaphore - Informatique Datenverarbeitung Metaphor Data processing Metapher (DE-588)4038935-2 gnd rswk-swf Datenverarbeitung (DE-588)4011152-0 gnd rswk-swf Metapher (DE-588)4038935-2 s Datenverarbeitung (DE-588)4011152-0 s DE-604 Perspectives in artificial intelligence 8 (DE-604)BV002492137 8 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=002686487&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Martin, James H. A computational model of metaphor interpretation Perspectives in artificial intelligence Métaphore - Informatique Datenverarbeitung Metaphor Data processing Metapher (DE-588)4038935-2 gnd Datenverarbeitung (DE-588)4011152-0 gnd |
| subject_GND | (DE-588)4038935-2 (DE-588)4011152-0 |
| title | A computational model of metaphor interpretation |
| title_auth | A computational model of metaphor interpretation |
| title_exact_search | A computational model of metaphor interpretation |
| title_full | A computational model of metaphor interpretation James H. Martin |
| title_fullStr | A computational model of metaphor interpretation James H. Martin |
| title_full_unstemmed | A computational model of metaphor interpretation James H. Martin |
| title_short | A computational model of metaphor interpretation |
| title_sort | a computational model of metaphor interpretation |
| topic | Métaphore - Informatique Datenverarbeitung Metaphor Data processing Metapher (DE-588)4038935-2 gnd Datenverarbeitung (DE-588)4011152-0 gnd |
| topic_facet | Métaphore - Informatique Datenverarbeitung Metaphor Data processing Metapher |
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