In this paper we propose research on how semantic web technologies can be used to mine the web, for information extraction. We also examine how new unsupervised processes can aid in extracting precise and useful information from semantic data, thus reducing the problem of information overload .The Semantic Web adds structure to the meaningful content of Web pages; hence information is given a welldefined meaning; which is both human readable as well as machine-processable. This enables the development of automated intelligent systems, allowing machines to comprehend the semantics of documents and data. Here we propose techniques for automating the process of search, analysis and categorization of semantic data, further we examine how these techniques can aid in improving the efficiency of already existing information retrieval technologies by implementing reporting functionalities, which is highlighted in the future work and challenges.
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