Topic Detection and Tracking

Event-based Information Organization

By: James Allan (Editor)

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Hardcover | 28 February 2002

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284 Pages

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The purposeofthis book is to providea recordofthe stateofthe art in Topic Detection and Tracking (TDT) in a single place. Research in TDT has been going on for about five years, and publications related to it are scattered all over the place as technical reports, unpublished manuscripts, or in numerous conference proceedings. The third and fourth in a series of on-going TDT evaluations marked a turning point in the research. As such. it provides an excellent time to pause. review the state of the art. gather lessons learned, and describe the open challenges. This book is a collection oftechnical papers. As such, its primary audience is researchers interested in the the current state of TDT research, researchers who hope to leverage that work sothat theirown efforts can avoid pointlessdu plication and false starts. It might also pointthem in the direction ofinteresting unsolved problems within the area. The book is also of interest to practition ers in fields that are related to TDT--e.g., Information Retrieval. Automatic Speech Recognition. Machine Learning, Information Extraction, and so on. In thosecases,TDTmay provide arich application domain for theirown research, or it might address similarenough problems that some lessons learned can be tweaked slightly to answer-perhaps partiallY-

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Non-Fiction Computing & I.T.Databases Information Retrieval Computer Science Artificial Intelligence Natural Language & Machine Translation Medicine Medicine in General Data Capture & Analysis

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Paperback

Published: 5th November 2012

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Preface	p. ix
Introduction to Topic Detection and Tracking	p. 1
Introduction	p. 1
TDT tasks	p. 3
History of TDT	p. 7
TDT 1999 and TDT 2000	p. 10
The Future of TDT	p. 13
Topic Detection and Tracking Evaluation Overview	p. 17
Introduction	p. 17
TDT Definitions: Stories, Events, and Topics	p. 18
TDT Corpora	p. 19
Evaluation Methodology	p. 20
Task Definitions	p. 25
Summary	p. 30
Corpora for Topic Detection and Tracking	p. 33
Introduction	p. 33
Overview of TDT Corpus Development	p. 35
Collection of Raw Data	p. 36
Transcription	p. 38
Story Segmentation	p. 39
Topic Definition	p. 42
Topic Annotation	p. 45
Corpus Formats	p. 54
Some Properties of the Corpus	p. 61
Conclusion	p. 64
Probabilistic Approaches to Topic Detection and Tracking	p. 67
Introduction	p. 67
Core TDT Technologies	p. 68
Corpus Processing	p. 75
Tracking	p. 75
Detection	p. 77
Crosslingual TDT	p. 80
Conclusions and Future Work	p. 81
Acknowledgments	p. 82
Multi-strategy Learning for TDT	p. 85
Introduction	p. 85
Segmentation	p. 87
Topic and Event Tracking	p. 88
Topic Detection	p. 96
First Story Detection	p. 99
Story Link Detection	p. 101
Multilingual TDT	p. 107
Concluding Remarks	p. 111
Statistical Models of Topical Content	p. 115
Introduction	p. 115
Models of Story Generation	p. 117
Tracking Systems	p. 120
Detection System	p. 128
Summary	p. 132
Segmentation and Detection at IBM	p. 135
Story Segmentation	p. 135
Topic Detection	p. 142
Acknowledgements	p. 147
A Cluster-Based Approach to Broadcast News	p. 149
Introduction	p. 149
Segmentation	p. 152
Detection	p. 154
Tracking	p. 163
Acknowledgements	p. 173
Signal Boosting for Translingual Topic Tracking	p. 175
Introduction	p. 176
The Signal-to-Noise Perspective	p. 177
Topic Tracking System Architecture	p. 178
Contrastive Conditions	p. 184
Conclusions and Future Work	p. 191
Acknowledgments	p. 194
Explorations Within Topic Tracking and Detection	p. 197
Introduction	p. 197
Basic System	p. 198
Tracking	p. 203
Cluster Detection	p. 205
First Story Detection	p. 208
Link Detection	p. 208
Bounds on Effectiveness	p. 216
Automatic Timeline Generation	p. 219
Conclusions	p. 222
Towards a "Universal Dictionary" for Multi-Language IR Applications	p. 225
Introduction	p. 225
Our TDT tracking algorithm	p. 229
The "Universal Dictionary" experiment	p. 236
Conclusions and Directions for Future Work	p. 239
An NLP & IR Approach to Topic Detection	p. 243
Introduction	p. 243
General System Framework	p. 245
Representation of News Stories and Topics	p. 246
Similarity and Interpretation of a Two-threshold Method	p. 248
Multilingual Topic Detection	p. 250
Development Experiments	p. 256
Evaluation	p. 259
Discussion	p. 261
Concluding Remarks and Future Works	p. 262
Index	p. 265
Table of Contents provided by Syndetics. All Rights Reserved.

Topic Detection and Tracking

Event-based Information Organization

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Hardcover

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