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Dedication    v
List of Figures    xi
Preface    xv
Acknowledgmentsxix
1. INTRODUCTION    1
2. RETRIEVAL STRATEGIES    9
  2.1 Vector Space Model    11
  2.2 Probabilistic Retrieval Strategies    21
  2.3 Language Models    45
  2.4 Inference Networks    57
  2.5 Extended Boolean Retrieval    67
  2.6 Latent Semantic Indexing    70
  2.7 Neural Networks    74
  2.8 Genetic Algorithms    80
  2.9 Fuzzy Set Retrieval    84
  2.10 Summary90
  2.11 Exercises91
3. RETRIEVAL UTILITIES    93
  3.1 Relevance Feedback    94
  3.2 Clustering    105
  3.3 Passage-based Retrieval    113
  3.4 N-grams    115
  3.5 Regression Analysis    119
  3.6 Thesauri    122
  3.7 Semantic Networks    132
  3.8 Parsing139
  3.9 Summary    146
  3.10 Exercises146
4.  CROSS-LANGUAGE INFORMATION RETRIEVAL    149
  4.1 Introduction    149
  4.2 Crossing the Language Barrier    151
  4.3 Cross-Language Retrieval Strategies    157
  4.4 Cross Language Utilities    170
  4.5 Summary178
  4.6 Exercises    179
5. EFFICIENCY181
  5.1 Inverted Index    182
  5.2 Query Processing    195
  5.3 Signature Files    199
  5.4 Duplicate Document Detection    203
  5.5 Summary208
  5.6 Exercises209
6. INTEGRATING STRUCTURED DATA AND TEXT    211
  6.1 Review of the Relational Model    215
  6.2 A Historical Progression    222
  6.3 Information Retrieval as a Relational Application    228
  6.4 Semi-Structured Search using a Relational Schema    245
  6.5 Multi-dimensional Data Model    250
  6.6 Mediators    250
  6.7 Summary    253
  6.8 Exercises    254
7. PARALLEL INFORMATION RETRIEVAL    257
  7.1 Parallel Text Scanning    258
  7.2 Parallel Indexing    263
  7.3 Clustering and Classification    270
  7.4 Large Parallel Systems    271
  7.5 Summary    272
  7.6 Exercises    274
8. DISTRIBUTED INFORMATION RETRIEVAL    275
  8.1 A Theoretical Model of Distributed Retrieval    276
  8.2 Web Search    281
  8.3 Result Fusion    284
  8.4 Peer-to-Peer Information Systems    286
  8.5 Other Architectures    289
  8.6 Summary    290
  8.7 Exercises    290
9. SUMMARY AND FUTURE DIRECTIONS    291
References    299
Index    331
List of Figures
  1.1 Document Retrieval    2
  1.2 Document Routing    3
  1.3 Result Set: Relevant Retrieved, Relevant, and Retrieved  4
  1.4 Precision and Two Points of Recall    5
  1.5 Typical and Optimal Precision/Recall Graph    5
  2.1 Vector Space Model    13
  2.2 Vector Space Model with a Two Term Vocabulary    14
  2.3 Inverted Index    17
  2.4 Training Data for Probabilistic Retrieval    25
  2.5 Language Model    46
  2.6 Simple Inference Network    58
  2.7 Document-Term-Query Inference Network    63
  2.8 Inference Network    64
  2.9 Neural Network with Feedback    76
  3.1 Relevance Feedback Process    95
  3.2 Document Clustering    106
  3.3 Overlapping vs Non-overlapping Passages    115
  3.4 Using a Thesaurus to Expand a Query    122
  4.1 Translate the Query    152
  4.2 Translate the Documents    153
  5.1 Inverted Index    183
  6.l IR as an Application of a RDBMS    213
  6.2 Intranet Mediator Architecture    254
  7.1 Partitioning an Inverted Index    264
  8.1 Distributed Document Retrieval    276
  8.2 Simple PageRank Calculation    283
  9.1 Sample TREC document    294
  9.2 Sample TREC query    294