Spotting and Discovering Terms through Natural Language Processing Review

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Spotting and Discovering Terms through Natural Language Processing ReviewA good book. Nice features:
1) Sweet reviews of related technologies and approaches
2) Pretty explicit description of his methodology
3) Well-written--clear and intelligible. I'm pretty hard to please in the intelligibility department (translation: "I don't have a strong background in this area"), and I found it quite easy to get through. Even pleasant--and that's saying a lot for a technical book.
Furthermore, he (at this time, at any rate) makes his source code available on line.Spotting and Discovering Terms through Natural Language Processing OverviewIn this book Christian Jacquemin shows how the power of natural languageprocessing (NLP) can be used to advance text indexing and information retrieval(IR). Jacquemin's novel tool is FASTR, a parser that normalizes terms and recognizesterm variants. Since there are more meanings in a language than there are words,FASTR uses a metagrammar composed of shallow linguistic transformations thatdescribe the morphological, syntactic, semantic, and pragmatic variations of wordsand terms. The acquired parsed terms can then be applied for precise retrieval andassembly of information.The use of a corpus-based unification grammar to define,recognize, and combine term variants from their base forms allows for intelligentinformation access to, or "linguistic data tuning" of, heterogeneous texts. FASTRcan be used to do automatic controlled indexing, to carry out content-based Websearches through conceptually related alternative query formulations, to abstractscientific and technical extracts, and even to translate and collect terms frommultilingual material. Jacquemin provides a comprehensive account of the method andimplementation of this innovative retrieval technique for text processing.

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