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 WWW: http://search.cpan.org/dist/Search-VectorSpace/