Abstract
The WWW Cache technology can store the popular WWW pages in the user’s places through which the browsers can speed up fetching these pages. The information in the WWW Cache shows the users’ recent interest. The users’ interest can be widely used: for example, to customize the WWW pages, to filter the information, to pre-fetch the information and so on. How to use the information in the WWW Cache effectively lies in how to build an adaptive user interest model and how to construct an adaptive algorithm for interest mining. The interest is really a fuzzy concept, but the granularity in simple interest model is too small to describe users’ interest appropriately. Based on the analysis of the WWW Cache model, we bring forward a rough-set-based describing method for users’ fuzzy interest. With this method, the web page and the set of web pages in the WWW cache can be modeled conformably, and the historical interest and the interest matching can be easily used.
This work was supported in part by the outstanding Young Scientist’s Fund of NSFC(60303024), the National Natural Science Foundation of China (NSFC) (90412003), National Grand Fundamental Research 973 Program of China (2002CB312000), Doctor Foundation of ministry of education(20020286004), Opening Foundation of Jiangsu Key Laboratory of Computer Information Processing Technology in Soochow University, Natural Science Research Plan for Jiang Su High School(04kjb520096), Doctor Foundatoin of Nanjing University of Posts and Telecommunications(2003-02 ).
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References
Wang, J.: A survey of WWW caching schemes for the internet. ACM Computer Communication Review 29(5), 36–46 (1999)
Carlos, C., Carlos, F.B.J.: Determining www user’s next access and its application to pre-fetching. In: Proceedings of ISCC 1997: The Second IEEE Symposium on Computers and Communications, Alexandria, Egypt, July 1-3, pp. 6–11 (1997)
Bestavros, A., Cunha, C.: A prefetching protocol using client speculation for the WWW. Boston University, Department of Computer Science, Boston, MA 02215, Tech.Rep:TR-95-011 (April 1995)
Kroeger, T.M., Long, D.D., Mogul, J.C.: Exploring the bounds of WWW latency reduction from caching and prefetching. In: Proceedings of the USENIX Symposium on Internet Technologies and Systems (USITS), Monterey, CA, pp. 13–22 (December 1997)
Barish, G., Obraczka, K.: World wide WWW caching: trends and techniques. IEEE Communications Magazine Internet Technology Series 38(5), 178–184 (2000)
Xu, B., Zhang, W., Chu, W.C., Yang, H.: Application of data mining in WWW pre-fetching. In: Proceedings of IEEE MSE 2000, TaiWan, pp. 372–377 (2000)
Xu, B., Zhang, W.: Research on WWW pre-fetching by data mining. Journal of Computer 24(4), 430–436 (2001)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual WWW search engine. In: Proc. of 7th world wide WWW conf. (www 1998), Brisbane, Australia, vol. 30, pp. 107–117 (1998)
Han, J., Men, X., et al.: Research on WWW mining. Journal of Computer Research and Development 38(4), 405–414 (2001)
Zhang, W., Xu, B., Chu, W.C., Yang, H.: Data mining algorithms for WWW pre-fetching. In: Proceedings of the 1st International Conference on WWW Information Systems Engineering(WISE 2000), Hong Kong, China, pp. 34–38 (2000)
Zhang, W., Xu, B., Song, W., Yang, H.: Pre-fetching WWW pages through data mining based prediction. Journal of Applied System Studies 3(2), 384–398 (2002)
Leggett, J., et al.: Special issues on hypertext. Communication of ACM 37(2), 26–108 (1994)
Chakrabarti, S., Dom, B., Raghavan, P., Rajagopalan, S., Gibson, D., Kleinberg, J.: Automatic resource compilation by analyzing hyperlinkage structure and associated text. In: Proceedings of the Seventh International World Wide Web Conference, pp. 65–74 (1998)
Zhang, W., Xu, B., Yang, H., Chu, W.C.: A genetic algorithm based general search engine. In: Proceedings of IEEE Multimedia Software Engineering 2000 (MSE 2000), TaiWan, pp. 366–371 (2000)
Zhang, W., Xu, B., Xu, L., et al.: Personalizing search result using agent. Mini-Micro Systems 22(6), 724–727 (2001)
Zhang, W., Xu, B.: Research on framework supporting web search engine. Journal of Computer Research & Development 37(3), 376–378 (2000)
Zhang, W., Xu, B., Zhou, X.: Counting techniques in web pages. Mini-Micro Systems 21(10), 1096–1099 (2000)
Zhang, W., Xu, B., Zhou, X.: Web page techniques for interacting between elements. Computer Engineering 26(8), 62–64 (2000)
Zhou, T., et al.: Information mining technologies and realization on WWW. Journal of Computer Research and Development 36(8), 1021–1024 (1999)
Zhang, W., Xu, B., Zhou, X.: An improved relativity technology in reference search. Journal of Software 12, 317–322 (2001)
Xu, B., Zhang, W.: Research on the improved reference search model. Journal of Computer Research and Development 39(5), 599–606 (2002)
Pawlak, Z.: Rough Sets. International Journal of Computer and Information Sciences 11(5), 341–356 (1982)
Zhang, D., Dong, Y.: An efficient algorithm to rank Web resources. In: Proceedings of the 9th International World Wide Web Conference, Amsterdam, Netherlands, pp. 449–455 (May 2000)
Wang, S.: Theory of fuzzy inference and fuzzy expert system. Shanghai Scientific Literature Press (1995)
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Zhang, W., Xu, B., Zhou, G. (2005). User’s Rough Set Based Fuzzy Interest Model in Mining WWW Cache. In: Chen, G., Pan, Y., Guo, M., Lu, J. (eds) Parallel and Distributed Processing and Applications - ISPA 2005 Workshops. ISPA 2005. Lecture Notes in Computer Science, vol 3759. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11576259_71
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DOI: https://doi.org/10.1007/11576259_71
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