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This module takes a list of documents (in English) and
builds a simple in-memory search engine using a vector
space model. Documents are stored as PDL objects, and
after the initial indexing phase, the search should be
very fast. This implementation applies a rudimentary
stop list to filter out very common words, and uses a
cosine measure to calculate document similarity.
All documents above a user-configurable similarity
threshold are returned.
Author: Maciej Ceglowski <maciej AT ceglowski.com>
WWW: http://search.cpan.org/dist/Search-VectorSpace/
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