Organization oriented web search management

Search engines play an important role in finding useful information on the Web. Many of the popular search engines are text-based and unable to understand the semantics of the posed query. Semantic Web promises to create both human and machine understandable data. A hybrid web search method which combines the powers of Semantic Web and traditional keyword-matching approaches is proposed in this paper. Ontology-based analysis of query keywords, their implicit relationships, and corresponding background knowledge are incorporated into the text-based web search process. The resulting search query provides a solution which improves current web searching results. Based on the Web search web services provided by Google, a prototype of meta-search engine which can intelligently ease and guide netizen´ s web searching efforts is initially implemented.