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.

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