Finding out about: a cognitive perspective on search engine technology and the WWW
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge Univ. Press
2000
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Table of contents Publisher description Inhaltsverzeichnis |
| Beschreibung: | Includes bibliograpical references (p.321-346) and index |
| Beschreibung: | XXVII, 356 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 0521630282 |
Internformat
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| 245 | 1 | 0 | |a Finding out about |b a cognitive perspective on search engine technology and the WWW |c Richard K. Belew |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge |b Cambridge Univ. Press |c 2000 | |
| 300 | |a XXVII, 356 S. |b Ill., graph. Darst. |e 1 CD-ROM (12 cm) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 500 | |a Includes bibliograpical references (p.321-346) and index | ||
| 650 | 7 | |a Cognitieve processen |2 gtt | |
| 650 | 7 | |a Information storage and retrieval |2 gtt | |
| 650 | 4 | |a Moteurs de recherche - Programmation | |
| 650 | 4 | |a Moteurs de recherche sur Internet | |
| 650 | 7 | |a Search engines |2 gtt | |
| 650 | 4 | |a Web - Logiciels | |
| 650 | 7 | |a World wide web |2 gtt | |
| 650 | 4 | |a Search engines |x Programming | |
| 650 | 4 | |a Web search engines | |
| 650 | 4 | |a World Wide Web |x Computer programs | |
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Datensatz im Suchindex
| _version_ | 1804132704847921152 |
|---|---|
| adam_text | Contents
Figures page xi
Foreword by C. J. van Rijsbergen xv
Preface xix
1 Overview 1
1.1 Finding Out About A Cognitive Activity 1
1.1.1 Working within the IR Tradition 8
1.2 Keywords 10
1.2.1 Elements of the Query Language 10
1.2.2 TopicalScope 11
1.2.3 Document Descriptors 12
1.3 Query Syntax 13
1.3.1 Query Sessions 14
1.4 Documents 16
1.4.1 Structured Aspects of Documents 19
1.4.2 Corpora 20
1.4.3 Document Proxies 20
1.4.4 Genre 21
1.4.5 BeyondText 22
1.5 Indexing 26
1.5.1 Automatically Selecting Keywords 27
1.5.2 Computer Assisted Indexing 28
1.6 FOA versus Database Retrieval 29
1.7 How Well Are We Doing? 34
1.8 Summary 36
2 Extracting Lexical Features 39
2.1 Building Useful Tools 39
2.2 Interdocument Parsing 40
2.3 Intradocument Parsing 42
2.3.1 Stemming and Other Morphological Processing 44
2.3.2 NoiseWords 47
2.3.3 Summary 48
2.4 Example Corpora 48
2.5 Implementation 50
2.5.1 Basic Algorithm 51
2.5.2 Fine Points 54
2.5.3 Software Libraries 58
3 Weighting and Matching against Indices 60
3.1 Microscopic Semantics and the Statistics of
Communication 60
3.2 Remember Zipf 62
3.2.1 Looking for Meaning in All the Wrong Places
(At the Character Level) 63
3.2.2 Zipf s Own Explanation 64
3.2.3 Benoit Mandelbrot s Explanation 66
3.2.4 Herbert Simon s Explanation 67
3.2.5 More Recent Zipfian Sightings 68
3.2.6 Summary 71
3.3 A Statistical Basis for Keyword Meaning 71
3.3.1 Lexical Consequences, Internal/External
Perspectives 71
3.3.2 Word Occurrence as a Poisson Process 73
3.3.3 Resolving Power 76
3.3.4 Language Distribution 78
3.3.5 Weighting the Index Relation 81
3.3.6 Informative Signals versus Noise Words 83
3.3.7 Inverse Document Frequency 84
3.4 Vector Space 86
3.4.1 Keyword Discrimination 88
3.4.2 Vector Length Normalization 89
3.4.3 Summary: SMART Weighting Specification 92
3.5 Matching Queries against Documents 93
3.5.1 Measures of Association 94
3.5.2 Cosine Similarity 95
3.6 Calculating TF IDF Weighting 96
3.7 Computing Partial Match Scores 97
3.8 Summary 101
4 Assessing the Retrieval 105
4.1 Personal Assessment of Relevance 106
4.1.1 Cognitive Assumptions 106
4.2 Extending the Dialog with RelFbk 109
4.2.1 Using RelFbk for Query Refinement 111
4.2.2 Using RelFbk to Adapt Documents Indices 115
4.2.3 Summary 116
4.3 Aggregated Assessment: Search Engine Performance 116
4.3.1 Underlying Assumptions 116
4.3.2 Consensual Relevance 118
4.3.3 Traditional Evaluation Methodologies 119
4.3.4 Basic Measures 122
4.3.5 Ordering the Retr Set 124
4.3.6 Normalized Recall and Precision 128
4.3.7 Multiple Retrievals across Varying Queries 129
4.3.8 One Parameter Criteria 132
4.3.9 Test Corpora 135
4.3.10 Other Measures 137
4.4 RAVE: A Relevance Assessment VEhicle 141
4.4.1 RAVeUnion 141
4.4.2 RAVePlan 142
4.4.3 Interactive RAVE 143
4.4.4 RAVeCompile 145
4.5 Summary 146
5 Mathematical Foundations 149
5.1 Derivation ofZipf s Law for Random Texts 149
5.1.1 Discussion 152
5.2 Dimensionality Reduction 153
5.2.1 A Simple Example 153
5.2.2 Formal Notions ofSimilarity 155
5.2.3 Singular Value Decomposition 156
5.2.4 How Many Dimensions k to Reduce to? 157
5.2.5 Other Uses ofVector Space 158
5.2.6 Computational Considerations 159
5.2.7 Latent Semantic Claims 159
5.3 Preference Relations 161
5.3.1 Multidimensional Scaling 161
5.3.2 Information in RelFbk 163
5.3.3 Connections between MDS and LSI 165
5.4 Clustering 165
5.4.1 The Cluster Hypothesis 165
5.4.2 Clustering Algorithms 166
5.5 Probabilistic Retrieval 167
5.5.1 Probability Ranking Principle 168
5.5.2 Bayesian Inversion 169
5.5.3 Odds Calculation 170
5.5.4 Binary Independence Model 170
5.5.5 Linear Discriminators 173
5.5.6 CostAnalysis 175
5.5.7 Bayesian Networks 175
6 Inference beyond the Index 182
6.1 Citation: Interdocument Links 185
6.1.1 Bibliometric Analysis of Science 187
6.1.2 TimeScale 190
6.1.3 Legal Citation 191
6.1.4 Citations and Arguments 193
6.1.5 Analyzing WWW Adjacency 195
6.2 Hypertext, Intradocument Links 199
6.2.1 Footnotes, Hyperfootnotes, and cf. 200
6.2.2 Hierarchie Containment 201
6.2.3 Argument Relations 205
6.2.4 Intra versus Interdocument Relations 207
6.2.5 Beyond Unary About (k) Predicates 209
6.3 Keyword Structures 210
6.3.1 Automatic Thesaurus Construction 211
6.3.2 Corpus Based Linguistics and WordNet 213
6.3.3 Taxonomies 217
6.4 Social Relations among Authors 220
6.4.1 AIGenealogy 221
6.4.2 An Empirical Foundation for a Philosophy
of Science 223
6.5 Modesof Inference 224
6.5.1 Theorem Proving Models for Relevance 224
6.5.2 Spreading Activation Search 225
6.5.3 Discovering Latent Knowledge within a Corpus 234
6.6 Deep Interfaces 238
6.6.1 Geographical Hitlists 238
6.7 FOA (The Law) 242
6.8 FOA (Evolution) 245
6.9 Text Based Intelligence 247
7 Adaptive Information Retrieval 252
7.1 Background 252
7.1.1 Training against Manual Indices 254
7.1.2 Alternative Tasks for Learning 255
7.1.3 Sourcesof Feedback 256
7.2 Building Hypotheses about Documents 258
7.2.1 Feature Selection 259
7.2.2 Hypothesis Spaces 262
7.3 Learning Which Documents to Route 263
7.3.1 Widrow Hoff 265
7.3.2 User Drift and Event Tracking 266
7.4 Classification 267
7.4.1 Modeling Documents 269
7.4.2 Training a Classifier 271
7.4.3 Priors 272
7.5 Other Approaches to Classification 273
7.5.1 Nearest Neighbor Matching 273
7.5.2 Boolean Predicates 273
7.5.3 When Irrelevant Attributes Abound 274
7.5.4 Combining Classifiers 275
7.5.5 Hierarchie Classification 277
7.6 Information Seeking Agents 279
7.6.1 Exploiting Linkage for Context 279
7.6.2 The InfoSpiders Algorithm 281
7.6.3 Adapting to Spatial Context 284
7.7 Other Learning Applications and Issues 286
7.7.1 Adaptive Lenses 286
7.7.2 Adapting to Fluid Language Use 288
7.8 Symbolic and Subsymbolic Learning 288
8 Conclusions and Future Directions 292
8.1 Things that Are Changing 292
8.1.1 WWWCrawling 294
8.2 Things that Stay the Same 298
8.2.1 The FOA Language Game 299
8.2.2 Sperber and Wilson s Relevance 304
8.2.3 Argument Structures 305
8.2.4 User as Portal 306
8.3 Who Needs to FOA 307
8.3.1 Authors 308
8.3.2 Scientists 309
8.3.3 The Changing Economics of Publishing 311
8.3.4 Teachers and Students 313
8.4 Summary 316
(Active) Colophon 318
Bibliography 321
Index 347
Figures
Finding Out About PaSe 1
1.1 The FOA Conversation Loop 5
1.2 Retrieval of Documents in Response to a Query 7
1.3 Assessment of the Retrieval 8
1.4 Schematic ofSearch Engine 10
1.5 A Query Session 15
1.6 Finding Out About POLITICAL FIDELITY 24
1.7 Obsolete Concert Schedule 25
1.8 Results of SCSI Search of UseNet 31
1.9 A Relevant Posting 31
1.10 Comparison of Retrieved versus Relevant Documents 35
2.1 Parsing Email and AIT to Common Specifications 42
2.2 Finite State Machine 43
2.3 AIT Year Distribution 49
2.4 Basic Postings Data Structures 53
2.5 Refined Postings Data Structures 54
2.6 STAIRS Posting Information 56
2.7 Quoted Lines in an Email Message 57
3.1 Zipfian Distribution of AIT Words 63
3.2 Rank/Frequency Distribution of Click Paths 70
3.3 Resolving Power 77
3.4 Specificity/Exhaustivity Trade Offs 78
3.5 Indexing Graph 80
3.6 Hypothetical Word Distributions 84
3.7 Vector Space 87
3.8 Length Normalization of Vector Space 90
3.9 Sensitivity of IDF to Document Size 90
3.10 Pivot Based Document Length Normalization 91
4.1 Relevance Scale 108
4.2 RelFbk Labeling of the Retr Set 109
4.3 Query Session, Linked by RelFbk HO
4.4 RelFbk Labels in Vector Space 112
4.5 VariousWaysof Being Irrelevant 112
4.6 UsingiteZFfcfctoRefine the Query 113
4.7 Document Modifications due to RelFbk 115
4.8 Consensual Relevance 119
4.9 Relevant versus Retrieved Sets 122
4.10 Recall/Precision Curve 127
4.11 Instability of Beginning of Re/Pre Curve 127
4.12 Best/Worst Retrieval Envelope 128
4.13 Normalized Recall 129
4.14 Multiple Queries, Fixed Recall Levels 130
4.15 11 Point Average Re/Pre Curves 131
4.16 TREC Query 136
4.17 Distinguishing between Overlapping Distributions 139
4.18 Operating Characteristic Curve 140
4.19 RAVE Interface 144
5.1 Lexicographic Tree Underlying Zipfian Distribution 150
5.2 aas Function of M, Number of Distinct Characters 152
5.3 Weight and Height Data Reduction 154
5.4 SVD Decomposition 157
5.5 Retrieval Performance as Function of SVD Dimension (/c) 158
5.6 Random Variables Underlying Binary Independence
Model 172
5.7 Interaction between Parental Influences 176
5.8 Bayesian Network Representation for FOA 177
5.9 Concept Matching Version of Bayesian Network 178
5.10 Two Examples of Query Modeling 179
6.1 Other Information Available for FOA 184
6.2 Basic Structureof Citations 186
6.3 Temporal Structure in Citations 188
6.4 Rose s Two Dimensional Analysis of Shepherd Treatment
Codes 194
6.5 Citation Expanded Hitlist 198
6.6 Containment and Document References 202
6.7 Correlation of Passages 203
6.8 Visualizing Topical Distributions 204
6.9 Topical Document Distributions 205
6.10 Intradocument Relations 206
6.11 FOAOverview 206
6.12 Typography Used to Isolate Talmudic Voices 208
6.13 HTML Version of the Talmud 209
6.14 Example of the Term LYMPHOMA within the MeSH
Keyword Thesaurus 212
6.15 Bipolar Organization ofAdjectives in WordNet 217
6.16 Nesting Taxonomies from Various Sources 218
6.17 A Sample of the AI Genealogical Record 222
6.18 Spreading Activation Search 226
6.19 Subnet Corresponding to Each Document 227
6.20 AIR Interface 229
6.21 Semantic Net of Legal Document Relations 234
6.22 Swanson s Search for Latent Knowledge 236
6.23 CIVIL WAR BATTLE Query, Standard Textual Hitlist 241
6.24 CIVIL WAR BATTLE Query, Geographical Presentation 242
6.25 The Long Life of Legal Documents 243
6.26 The Annotation Relation between Text and Sequence
Data 246
7.1 Learning Conceptual Structures 253
7.2 Browsing across Queries in Same Session 257
7.3 Inductive Bias 263
7.4 Document Modifications due to RelFbk 264
7.5 Training a Classifier 268
7.6 RIPPER Classification Rule 273
7.7 Covering Algorithms 274
7.8 Combining Experts 275
7.9 Optimal Weightings Distribution 276
7.10 Hierarchie Classification 278
7.11 AncestorsofaClass 279
7.12 AdaptiveLens 287
8.1 Crawler Coverage 295
8.2 A Semiotic View of FOA 301
8.3 A Semiotic Analysis of Keyword Mismatch 302
8.4 Grice s Maxims 303
8.5 Query as Portal, Connecting Corpora 307
8.6 TheTell/AskDuality 314
|
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| author | Belew, Richard K. |
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| callnumber-sort | TK 45105.884 |
| callnumber-subject | TK - Electrical and Nuclear Engineering |
| classification_rvk | ST 205 ST 273 |
| ctrlnum | (OCoLC)43384693 (DE-599)BVBBV014720138 |
| dewey-full | 025.04 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 025 - Operations of libraries and archives |
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| dewey-search | 025.04 |
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| discipline | Allgemeines Informatik |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV014720138 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T19:57:03Z |
| institution | BVB |
| isbn | 0521630282 |
| language | English |
| lccn | 99087329 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-012766286 |
| oclc_num | 43384693 |
| open_access_boolean | |
| owner | DE-945 DE-634 DE-11 |
| owner_facet | DE-945 DE-634 DE-11 |
| physical | XXVII, 356 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | Belew, Richard K. Verfasser (DE-588)141866314 aut Finding out about a cognitive perspective on search engine technology and the WWW Richard K. Belew 1. publ. Cambridge Cambridge Univ. Press 2000 XXVII, 356 S. Ill., graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Includes bibliograpical references (p.321-346) and index Cognitieve processen gtt Information storage and retrieval gtt Moteurs de recherche - Programmation Moteurs de recherche sur Internet Search engines gtt Web - Logiciels World wide web gtt Search engines Programming Web search engines World Wide Web Computer programs Information Retrieval (DE-588)4072803-1 gnd rswk-swf Suchmaschine (DE-588)4423007-2 gnd rswk-swf World Wide Web (DE-588)4363898-3 gnd rswk-swf Kognitive Orientierung (DE-588)4134004-8 gnd rswk-swf Suchmaschine (DE-588)4423007-2 s Information Retrieval (DE-588)4072803-1 s Kognitive Orientierung (DE-588)4134004-8 s DE-604 World Wide Web (DE-588)4363898-3 s 1\p DE-604 http://www.loc.gov/catdir/toc/cam023/99087329.html Table of contents http://www.loc.gov/catdir/description/cam0210/99087329.html Publisher description HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012766286&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Belew, Richard K. Finding out about a cognitive perspective on search engine technology and the WWW Cognitieve processen gtt Information storage and retrieval gtt Moteurs de recherche - Programmation Moteurs de recherche sur Internet Search engines gtt Web - Logiciels World wide web gtt Search engines Programming Web search engines World Wide Web Computer programs Information Retrieval (DE-588)4072803-1 gnd Suchmaschine (DE-588)4423007-2 gnd World Wide Web (DE-588)4363898-3 gnd Kognitive Orientierung (DE-588)4134004-8 gnd |
| subject_GND | (DE-588)4072803-1 (DE-588)4423007-2 (DE-588)4363898-3 (DE-588)4134004-8 |
| title | Finding out about a cognitive perspective on search engine technology and the WWW |
| title_auth | Finding out about a cognitive perspective on search engine technology and the WWW |
| title_exact_search | Finding out about a cognitive perspective on search engine technology and the WWW |
| title_full | Finding out about a cognitive perspective on search engine technology and the WWW Richard K. Belew |
| title_fullStr | Finding out about a cognitive perspective on search engine technology and the WWW Richard K. Belew |
| title_full_unstemmed | Finding out about a cognitive perspective on search engine technology and the WWW Richard K. Belew |
| title_short | Finding out about |
| title_sort | finding out about a cognitive perspective on search engine technology and the www |
| title_sub | a cognitive perspective on search engine technology and the WWW |
| topic | Cognitieve processen gtt Information storage and retrieval gtt Moteurs de recherche - Programmation Moteurs de recherche sur Internet Search engines gtt Web - Logiciels World wide web gtt Search engines Programming Web search engines World Wide Web Computer programs Information Retrieval (DE-588)4072803-1 gnd Suchmaschine (DE-588)4423007-2 gnd World Wide Web (DE-588)4363898-3 gnd Kognitive Orientierung (DE-588)4134004-8 gnd |
| topic_facet | Cognitieve processen Information storage and retrieval Moteurs de recherche - Programmation Moteurs de recherche sur Internet Search engines Web - Logiciels World wide web Search engines Programming Web search engines World Wide Web Computer programs Information Retrieval Suchmaschine World Wide Web Kognitive Orientierung |
| url | http://www.loc.gov/catdir/toc/cam023/99087329.html http://www.loc.gov/catdir/description/cam0210/99087329.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012766286&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT belewrichardk findingoutaboutacognitiveperspectiveonsearchenginetechnologyandthewww |