Document (#37121)

Author
Jacquemin, C.
Title
Spotting and discovering terms through natural language processing
Imprint
Cambridge, MA : MIT Press
Year
2001
Pages
VIII, 378 S
Isbn
0-262-10085-1
Abstract
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. The use of a corpus-based unification grammar to define, recognize, and combine term variants from their base forms allows for intelligent information access to, or "linguistic data tuning" of, heterogeneous texts. FASTR can be used to do automatic controlled indexing, to carry out content-based Web searches through conceptually related alternative query formulations, to abstract scientific and technical extracts, and even to translate and collect terms from multilingual material. Jacquemin provides a comprehensive account of the method and implementation of this innovative retrieval technique for text processing.
Footnote
Rez. in: KO 28(2001) no.3, S.152-154 (L. Da Sylva)
Theme
Computerlinguistik
Object
FASTR
LCSH
Language and languages / Variation / Data processing
Terms and phrases / Data processing
RSWK
Automatische Indexierung  / Computerlinguistik  / Information Retrieval
Syntaktische Analyse (GBV)
Textverstehendes System (HBZ)
Computerlinguistik / Sprachvariante (HBZ)
BK
54.75
18.04
17.52
17.46
DDC
418
GHBS
BFP (FH K)
BFP (DU)
TZF (DU)
TVV (DU)
LCC
P305.18.D38J33 2001
RVK
ES 965

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