FastKwic, an “Intelligent“ Concordancer Using FASTR

8596

Authors

nan

Abstract

AbstractIn this paper, we introduce the FastKwic (Key Word In Context using FASTR), a new concordancer for French and English that does not require users to learn any particular request language. Built on FASTR, it shows them not only occurrences of the searched term but also of several morphological, morpho-syntactic and syntactic variants (for example, image enhancement, enhancement of image, enhancement of fingerprint image, image texture enhancement). Fastkwic is freely available. It consists of two UTF-8 compliant Perl modules that depend on several external tools and resources : FASTR, TreeTagger, Flemm (for French). Licenses of theses tools and resources permitting, the FastKwic package is nevertheless self-sufficient. FastKwic first modules is for terminological resource compilation. Its input is a list of terms - as required by FASTR. FastKwic second module is for processing concordances. It relies on FASTR again for indexing the input corpus with terms and their variants. Its output is a concordancer: for each term and its variants, the context of occurrence is provided.

Keywords

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Full Content

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Labeled Text

AbstractIn this paper, we introduce the FastKwic (Key Word In Context using FASTR), a new concordancer for French and English that does not require users to learn any particular request language. Built on FASTR, it shows them not only occurrences of the searched term but also of several morphological, morpho-syntactic and syntactic variants (for example, image enhancement, enhancement of image, enhancement of fingerprint image, image texture enhancement). Fastkwic is freely available. It consists of two UTF-8 compliant Perl modules that depend on several external tools and resources : FASTR, TreeTagger, Flemm (for French). Licenses of theses tools and resources permitting, the FastKwic package is nevertheless self-sufficient. FastKwic first modules is for terminological resource compilation. Its input is a list of terms - as required by FASTR. FastKwic second module is for processing concordances. It relies on FASTR again for indexing the input corpus with terms and their variants. Its output is a concordancer: for each term and its variants, the context of occurrence is provided.

Publication Details

Paper ID:
8596
Year:
2010
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan