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Published Articles >> Table of Contents >> Abstract
2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
pp. 503-506
Using Element and Document Profile for Information Clustering
Jun Lai, La Trobe University Bundoora
Ben Soh, La Trobe University Bundoora
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/EEE.2004.1287354
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| Abstract |
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The tremendous growth in the amount of information available and the number of visitors to web sites in the recent years poses some key challenges for information filtering and retrieval. Web visitors not only expect high quality and relevant information, but also wish that the information be presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate an index called document similarity score based on elements of the document. Using the index, document profile will be derived. Any documents with the similarity score above a given threshold will be clustered. Using these pre-clustered documents, information filtering and retrieval can be made more efficient.
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 Additional Information
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Index Terms- elements, clustering, information filtering, information retrieval, search engine, World Wide Web
Citation:
Jun Lai, Ben Soh,
"Using Element and Document Profile for Information Clustering,"
eee,
pp. 503-506,
2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04),
2004
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