Discovering semantic proximity for web pages
Dynamic Nearness is a data mining algorithm that detects semantic relationships between objects in a database, based on access patterns. This approach can be applied to web pages to allow automatic dynamic reconfiguration of a web site. Worst-case storage requirements for the algorithm are quadratic (in the number of web pages), but practical reductions, such as ignoring a few long transactions that provide little information, drop storage requirements to linear. Thus, dynamic nearness scales to large systems. The methodology is validated via experiments run on a moderately-sized existing web site.
Keywordslearnign and knowledge discovery intelligent information systems semantic distance metrics data mining world wide web
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- 1.M. S. Chen, J. S. Park, and. P. S. Yu, “Data mining for path traversal patterns in a web environment’, Proc. 16th International Conference on Distributed Computing Systems, pages 385–392, 1996.Google Scholar
- 2.R. Cooley, B. Mobasher, and J. Srivastava, “Grouping Web Page References into Transactions for Mining World Wide Web Browsing Patterns,” Proceedings of the IEEE Knowledge and Data Engineering Exchange Workshop, KDEX, pages 2–9, 1997.Google Scholar
- 4.F Cuppers and R. Demolombe, “Cooperative answering: a methodology to provide intelligent access to databases”, Proc. 2nd International Conference on Expert Database Systems, Virginia, USA, 1988.Google Scholar
- 5.T. Gaasterland, P. Godfrey, and J. Minker, “An overview of cooperative answering”, In Nonstandard Queries and Nonstandard Answers. R. Demolombe and T. Imielinski, eds. Oxford Science Publications, 1994.Google Scholar
- 6.C. M. Hymes and G. M. Olson, “Quick but not so dirty web design: applying empirical conceptual clustering techniques to organize hypertext content” Proceedings of the Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques. pages 159–162, 1997.Google Scholar
- 8.L. Leydesdorff and R. Zaal, “Co-words and citations relations between document sets and environments,” Informetrics 87/88, pages 105–119, 1988.Google Scholar
- 9.M. A. Merzbacher and W. W. Chu, “Query-Based Semantic Nearness for Cooperative Query Answering”, Proc. 1st ISMM Conference on Information and Knowledge Management: CIKM, 1993.Google Scholar
- 11.G. Salton, Automatic text processing: the transformation, analysis, and retrieval of information by computer, Addison-Wesley, Reading Massachusetts, 1989.Google Scholar
- 12.D. G. Zhao, “ELINOR electronic library system”, Electronic Library, pages 289–294, Oct 1994.Google Scholar