A web page ranking method by analyzing hyperlink structure and k-elements
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part IV
Turning mass media to your media: intelligent search with customized results
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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The tremendous growth in the amount of informationavailable and the number of visitors to web sites in therecent years poses some key challenges for informationfiltering and retrieval. Web visitors not only expect highquality and relevant information, but also wish that theinformation be presented in an as efficient way aspossible. The traditional filtering methods, however,only consider the relevant values of document. Theseconventional methods fail to consider the efficiency ofdocuments retrieval. In this paper, we propose a newalgorithm to calculate an index called documentsimilarity score based on elements of the document.Using the index, document profile will be derived. Anydocuments with the similarity score above a giventhreshold will be clustered. Using these pre-clustereddocuments, information filtering and retrieval can bemade more efficient.