Available online at: www.ijarcsse.com Ontology Based Information Retrieval Model in Semantic Web: A Review

Abstract — World Wide Web is the largest database in the Universe which is mostly understandable by human users and not by machines. It lacks the existence of a semantic structure which maintains interdependency of its components. Presently, search on web is keyword based i.e., information is retrieved on the basis of text search of all available matching URL’s / hyperlinks. This may result in the presentation of irrelevant information to the user. In the current web, resources are accessible through hyperlinks to web content spread throughout the world. These links make the physical connections and are not understood by the machines. So there is a lack of relationships which captures the meaning of the links for the machines to understand. The explosion of unstructured data on the world wide-web has generated significantly further interest in the extraction problem, and helped position it as central research goal in the Database, Artificial Intelligence, Data Mining, Information Extraction, Natural Language Processing, and Web communities. Hence information extraction is a logical step to retrieve structured data and the extracted information. Information retrieval is synonymous with “determination of relevance”. Information retrieval is described as the task of identifying documents in the collection on the basis of properties approved to the documents by the user requesting the retrieval. This paper presents the literature review Semantic Web Mining, our vision combining the three research areas Semantic Web, Mining and Multi Agent Systems. The basic idea is to improve th