An edition of Spotting and discovering terms through natural language processing (2001)

Spotting and discovering terms through natural language processing

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Last edited by MARC Bot
November 13, 2023 | History
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An edition of Spotting and discovering terms through natural language processing (2001)

Spotting and discovering terms through natural language processing

by

  • ★★★★★ 5.00 ·
  • 1 Rating
  • 2 Want to read
  • 0 Currently reading
  • 1 Have read

"In this book Christian Jacquemin shows how the power of natural language processing (NLP) can be used to advance text indexing and information retrieval (IR). Jacquemin's novel tool is FASTR, a parser that normalizes terms and recognizes term variants. Since there are more meanings in a language than there are words, FASTR uses a metagrammar composed of shallow linguistic transformations that describe the morphological, syntactic, semantic, and pragmatic variations of words and terms.

The acquired parsed terms can then be applied for precise retrieval and assembly of information."--BOOK JACKET.

Publish Date
Publisher
MIT Press
Language
English
Pages
378

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Previews available in: English

Subjects
Data processing, Language and languages, Terms and phrases, Variation

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Edition Availability
Cover of: Spotting and discovering terms through natural language processing
Spotting and discovering terms through natural language processing
2001, MIT Press
in English
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Book Details

Table of Contents

Machine generated contents note: 1 Introduction
1.1 Motivation
1.2 Term Spotting through Term Normalization
1.3 Is In-depth Understanding a Viable Alternative?
1.4 Term Variation: A Central Issue
1.5 Overview of the Study
2 Studies in Term Extraction
2.1 Basic Concepts and Techniques
2.2 Term Acquisition
2.3 Parsers for Phrase Indexing
2.4 FASTR, Exploiting Term Variation in Term Spotting
3 Terms
3.1 FASTR Formalism
3.2 Morphology
3.3 Extended Domain of Locality and Lexicalization
3.4 Derivation within FASTR
3.5 Parsing with FASTR
3.6 Summary
4 Variations
4.1 Linguistic Analysis of Term Variations
4.2 Description of Variations through Metarules
4.3 A Constructive View of Metarules
4.4 Summary
5 Experimental Tuning
5.1 Elementary Variations of Binary Terms
5.2 Elementary Variations of n-ary Terms
5.3 Compositions of Elementary Variations
5.4 Refining Metarules
5.5 Evaluating Syntactic Metarules
5.6 Summary
6 Term Enrichment
6.1 Automatic Thesaurus Acquisition
6.2 Statistical Acquisition from Variations
6.3 Term Enrichment from Variations
6.4 Summary
7 Morphosyntactic Variants
7.1 Morphological Links and Regular Expressions in FASTR
7.2 Evaluation of Morphosyntactic Variant Extraction
7.3 Evaluating Morphosyntactic Metarules
7.4 Summary
8 Semantic Variation and Applications
8.1 Semantic Variation
8.2 Applications
8.3 Other Interesting Directions
9 Conclusion
A Metarule Files
A.1 Paradigmatic Syntactic Metarules
A.2 Filtering Syntactic Metarules
A.3 Paradigmatic Morphosyntactic Metarules
A.4 Filtering Morphosyntactic Metarules
A.5 Filtering Semantic and Morphosemantic Metarules
A.6 Pattern Extractors
B Structured Acquisitions
C Corpus and Term Lists
D Grammar Files
Glossary
Notes
References
Author Index
Subject Index.

Edition Notes

Includes bibliographical references (p. [353]-368) and index.

Published in
Cambridge, Mass

Classifications

Dewey Decimal Class
418
Library of Congress
P305.18.D38 J33 2001

The Physical Object

Pagination
viii, 378 p. :
Number of pages
378

ID Numbers

Open Library
OL6801985M
Internet Archive
spottingdiscover0000jacq
ISBN 10
0262100851
LCCN
00135245
OCLC/WorldCat
44877022
Goodreads
4063158

Source records

amazon.com record
Library of Congress MARC record
Internet Archive item record
Promise Item
marc_columbia MARC record

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
November 13, 2023 Edited by MARC Bot import existing book
January 15, 2023 Edited by ImportBot import existing book
August 20, 2021 Edited by MARC Bot import existing book
July 29, 2020 Edited by MARC Bot import existing book
April 1, 2008 Created by an anonymous user Imported from Scriblio MARC record