SEMANTIC WEB BASED SEARCH AGENT SYSTEM

The term "search engine” is traditionally used to refer to crawler based search engines, manually maintained directories, and hybrid search engines. However, current search engines do not fully satisfy the users' needs especially in terms of accuracy and specificity of the results. This paper proposes an approach to build an intelligent search agent system on top of the Semantic Web. The presented system consists of five main parts: the Annotator, the Ontology Parser, the Indexer, the Search Agent, and the Data Repository. Two kinds of search are implemented: keyword based and concept based search. The keyword based search matches a user’s query terms to concepts while concept based search allows a user to choose the concept that s/he want to search for together with some attributes for this concept.