Online Granular Prediction Model for Web Prefetching

摘要：

Web prefetching is a primary means to reduce user access latency.The PPM was used to predict user request patterns in traditional literature.However the existing PPM models are usually constructed in offiine case,they could not be updated incrementally for user coming new request,such models are only suitable for the relatively stable user access patterns.In this paper,we present an online PPM granular prediction model to capture the changing patterns and the limitation of memory,its implementation is based on a noncompact suffix tree and a sliding window W,the results show that our granular prediction model gives the best result comparing with existing PPM prediction models.

关键词： Granular Computing Data Mining Algorithms

作者: Zhimin Gu Zhijie Ban Hongli Zhang Zhaolei Duan Xiaojin Ren

作者单位: School of Computer Science and Technology,Beijing Institute of Technology,P.R.China

会议类型: 国际会议

会议名称: The Third International Conference on Rough Sets and Knowledge Tevhnology(RSKT 2008)(第三届粗糙集与知识技术国际会议)

会议地点: 成都

会议语种:英文

页码: 340-347

在线出版日期: 2008-05-17（万方平台首次上网日期，不代表论文的发表时间）