Building a Semantic Web Search Engine: Challenges and Solutions

Abstract

Current web search engines return links to documents for user-specified keywords queries. Users have to then manually trawl through lists of links and glean the required information from documents. In contrast, semantic search engines allow more expressive queries over information integrated from multiple sources, and return specific information about entities, for example people, locations, news items. An entity-centric data model furthermore permits powerful query and browsing techniques. In this paper, we report on our experiences in collecting and integrating Web data from millions of sources, and describe both application-developer query services and end-user navigation services offered by SWSE, the Semantic Web Search Engine.