Architecting a search engine for the semantic web

Since its emergence in the early 1990s, the World Wide Web has rapidly evolved into a global information space of incomparable size. Keyword-based search engines such as Google ™ index as many webpages as possible for the benefit of human users. Sophisticated as such search engines have become, they are still often unable to bridge the gap between HTML and the human. Tim Berners-Lee envisions the Semantic Web as the web of machine-interpretable information that complements the existing World Wide Web, providing an automated means for machines to truly traverse the Web on behalf of their human counterparts. A cornerstone application of the emerging Semantic Web is the search engine that is capable of tying components of the Semantic Web together into a traversable landscape. This paper describes both an architecture for and a prototype of a Semantic Web Search Engine (SWSE) using Jena that provides more sophisticated searching with more exacting results. To compare keyword-based search via Google with semantics-based search via the SWSE prototype, we utilize the Google CruciVerbalist (GCV), a system we developed that attempts to solve crossword puzzles via a generic search interface