PISCES delivers full text search across enormous databases with unified relevance-ranked results, providing full control over your search algorithm, on Windows or Unix.

Combines the advantages of traditional relevancy ranking algorithms with a proprietary algorithm for ranking based on word proximity as well as standard Boolean operations. PISCES is used with unstructured textual data in addition to highly structured data such as XML-encoded documents and MARC records. It searches multiple databases in any combination, yielding combined ranked result lists. It consists of a library of search and retrieval subroutines which may be combined to produce .NET as well as stand-alone retrieval systems.

Turn to PISCES to improve access to information using powerful relevance-ranking capabilities, advanced search features, and simple ways to filter search results by category or FAQs.

Why is it better?

PISCES is fast, proven, and flexible. PISCES ranks information based upon three factors: the number of unique query terms in a document, automatic term weighting based on a standard term frequency - inverse document frequency (TfIdf) algorithm, and proximity weighting. These three factors can be weighted in their effect on the final ranking. A retrieval language is used where reserved words are preceded by an 'at' (@) sign. For more technical information, visit PISCES Technical Manual.

Document Similarity and Comparative Analysis Technology

PISCES has also been used to quickly identify similar documents and to compare documents to identify similar text and calculate/display their similarities in side-by-side comparisons.