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Text-based intelligent Systems

Current Research and Practice in information Extraction and Retrieval

By: Paul S. Jacobs (Editor)

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Hardcover | 1 July 1992 | Edition Number 1

At a Glance

Hardcover
290 Pages

Dimensions(cm)
22.9 x 15.2 x 2.13

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The symposium on which this volume was based brought together approximately fifty scientists from a variety of backgrounds to discuss the rapidly-emerging set of competing technologies for exploiting a massive quantity of textual information. This group was challenged to explore new ways to take advantage of the power of on-line text. A billion words of text can be more generally useful than a few hundred logical rules, if advanced computation can extract useful information from streams of text and help find what is needed in the sea of available material. While the extraction task is a hot topic for the field of natural language processing and the retrieval task is a solid aspect in the field of information retrieval, these two disciplines came together at the symposium and have been cross-breeding more than ever.

The book is organized in three parts. The first group of papers describes the current set of natural language processing techniques used for interpreting and extracting information from quantities of text. The second group gives some of the historical perspective, methodology, and current practice of information retrieval work; the third covers both current and emerging applications of these techniques. This collection of readings should give students and scientists alike a good idea of the current techniques as well as a general concept of how to go about developing and testing systems to handle volumes of text.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Natural Language & Machine Translation Psychology Cognition & Cognitive Psychology Business Applications Word Processing Software

Preface	p. vii
Introduction Text Power and Intelligent Systems	p. 1
Bibliography	p. 8
Abstract	p. 8
Broad-Scale NLP	p. 9
Robust Processing of Real-World Natural-Language Texts	p. 13
Introduction	p. 13
Abstract	p. 13
Conclusion	p. 30
Bibliography	p. 31
Acknowledgments	p. 31
Combining Weak Methods in Large-Scale Text Processing	p. 35
Conclusion	p. 54
Bibliography	p. 55
Mixed-Depth Representations for Natural Language Text	p. 59
Acknowledgments	p. 79
Bibliography	p. 79
Conclusion	p. 79
Robust Partial-Parsing Through Incremental, Multi-Algorithm Processing	p. 83
Introduction	p. 83
Bibliography	p. 97
Abstract	p. 101
Corpus-Based Thematic Analysis	p. 101
Conclusions	p. 119
Bibliography	p. 119
""""Traditional"""" Information Retrieval	p. 123
Introduction	p. 127
Text Retrieval and Inference	p. 127
Abstract	p. 127
Bibliography	p. 149
Assumptions and Issues in Text-Based Retrieval	p. 157
Introduction	p. 157
Conclusion	p. 172
Bibliography	p. 174
Text Representation for Intelligent Text Retrieval: A Classification-Oriented VIew	p. 179
Introduction	p. 179
Conclusion	p. 193
Acknowledgments	p. 193
Bibliography	p. 194
Abstract	p. 199
Automatic Text Structuring Experiments	p. 199
Emerging Applications	p. 211
Statistical Methods, Artificial Intelligence, and Information Retrieval	p. 215
Introduction	p. 215
Bibliography	p. 222
Intelligent High-Volume Text Processing Using Shallow, Domain-Specific Techniques	p. 227
Abstract	p. 227
Conclusion	p. 239
Bibliography	p. 240
Automatically Constructing Simple Help Systems from Natural Language Documentation	p. 243
Abstract	p. 243
Introduction	p. 244
Conclusion	p. 254
Bibliography	p. 254
Introduction	p. 257
Direction-Based Text Interpretation as An Information Access Refinement	p. 257
Abstract	p. 257
Conclusions	p. 272
Acknowledgments	p. 273
Bibliography	p. 273
Index	p. 275
Table of Contents provided by Publisher. All Rights Reserved.

Text-based intelligent Systems

Current Research and Practice in information Extraction and Retrieval

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

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