ABSTRACT

With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general-purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming this limitation. Several search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of Semantic Web resources, that is, relations. To make the Semantic Web work, well-structured data and rules are necessary for agents to roam the Web [2]. XML and RDF are two important technologies: we can create our own structures by XML without indicating what they mean; RDF uses sets of triples which express basic concepts [2]. DAML is the extension of XML and RDF The aim of this project is to develop a search engine based on ontology matching within the Semantic Web. It uses the data in Semantic Web form such as DAML or RDF. When the user input a query, the program accepts the query and transfers it to a machine learning agent. Then the agent measures the similarity between different ontology’s, and feedback the matched item to the user.