Publications: Spotting and Discovering Terms through Natural Language Processing

alexis nasr alexis.nasr at
Mon Jun 25 16:03:51 UTC 2001

Spotting and Discovering Terms through Natural Language Processing

Christian Jacquemin


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.

Christian Jacquemin is Professor at the University of Paris 11 and
Researcher in Computer Science at CNRS-LIMSI (Centre National de la
Recherche Scientifique, Laboratoire d'Informatique pour la Mécanique et les
Sciences de l'Ingénieur).

7 x 9, 357 pp., 71 illus., cloth, ISBN 0-262-10085-1

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