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基于深度优先序列模式挖掘的预取模型

Prefetching model based on depth-first sequential pattern mining
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摘要 序列模式挖掘能够发现隐含在Web日志中的用户的访问规律,可以被用来在Web预取模型中预测即将访问的Web对象。目前大多数序列模式挖掘是基于Apriori的宽度优先算法。提出了基于位图深度优先挖掘算法,采用基于字典树数据结构的深度优先策略,同时采用位图保存和计算各序列的支持度,能够较迅速地挖掘出频繁序列。将该序列模式挖掘算法应用于Web预取模型中,在预取缓存一体化的条件下实验表明具有较好的性能。 Sequential pattern mining can find the user access patterns hidden in the Web log,which can be used to predict the upcoming Web access objects in the Web prefetching modeLMost sequential pattern mining algorithms are based on Apriori breadth-first search strategy.A new sequential pattern algorithm based on depth-first search strategy is introduced and the mining mechanism based on lexicographic tree is presented in this paper.The data structure of bitmap is used in order to save and calculate the support of sequences fast.By the use of which,a prefetching model is proposed in integrated Web prefetching and caching environment.The experimental results show that the prefetching model based on depth-first sequential pattern mining can have a good performance.
作者 卫琳 石磊
出处 《计算机工程与应用》 CSCD 北大核心 2007年第20期169-172,共4页 Computer Engineering and Applications
基金 国家自然科学基金(the National Natural Science Foundation of China under Grant No.60472044) 河南省高等学校信息网络重点实验室开放基金
关键词 序列模式 深度优先 WEB缓存 WEB预取 WEB挖掘 sequential pattern depth first Web cache Web prefetching Web mining
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参考文献8

  • 1Yan-Bo Han Zhi-Wei Xu Hai Zhuge.Preface[J].Journal of Computer Science & Technology,2006,21(4):465-465. 被引量:18
  • 2Agrawal R,Srikant R.Mining sequential patterns[C]//Proc International Conference on Data Engineering,Taipei,1995:3-14.
  • 3Pei J,Han J,Pinto H,et al.PrefixSnan:mining sequential patterns efficiently by prefix-projected patten growth[C]//Proc of International Conference on Data Engineering,2001.
  • 4Agrawal R,Aggarwal C,Prasad V V V.A Tree projection algorithm for generation frequent itemsets[J].Journal of Parallel and Distributed Computing,2001,61:350-361.
  • 5Burdick D,Calimlim M,Gehrke J.Mafia:a maximal frequent itemset algorithm for transactional databases[C]//Proc of ICDE 2001,Heidelberg,2001.
  • 6Ayres J,Gehrke J E,Yiu T,et al.Sequential pattern mining using bitmaps[C]//Proc of SIGKDD Int'l Conf on Knowledge Discovery and Data Mining,July 2002.
  • 7石磊,张岳,裴云霞,古志民.基于Web对象流行度的PPM预测模型[J].小型微型计算机系统,2006,27(7):1378-1382. 被引量:9
  • 8Web caching and content delivery resources[EB/OL].http://www.web-caching.com/.

二级参考文献11

  • 1Thomas MK,Darrel DEL,Jeffrey CM.Exploring the bounds of Web latency reduction from caching and prefetching[C].In:Proceedings of the USENIX Symposium on Internet Technologies and Systems.California,1997,13-22.
  • 2Crovella M,Barford P.The network effects of prefetching[C].In:Proceedings of the IEEE Conference on Computer and Communications.San Francisco,1998,1232-1240.
  • 3Palpanas T,Mendelzon A.Web prefetching using partial match prediction[C].In:Proceedings of Web Caching Workshop.San Diego,California,March 1999.
  • 4Pitkow J,Pirolli P.Mining longest repeating subsequences to predict World Wide Web surfing[C].In:Proceedings of Usenix Technical Conference.Brisbane,Australia,1999,139-150.
  • 5Busari M,Williamson C.On the sensitivity of Web proxy cache performance to workload characteristics.In:IEEE Infocom 2001,Anchorage,2001,1225-1234.
  • 6Cleary J G,Witten I H.Data compression using adaptive coding and partial string matching[J].IEEE Transactions on Communications,1984,32(4):396-402.
  • 7Shi Lei,Gu Zhi-min,Wei Lin,Shi Yun.Popularity-based selective markov model[C].In:Proceedings of IEEE/ WIC/ ACM Web Intelligence,Beijing,Sept.2004,504-507.
  • 8Breslau L,Cao P,Fan L,Phillips G et al.Web caching and Zipf-like distributions:evidence and implications[C].In:Proceedings of IEEE INFOCOM '99.New York,March 1999,126-134.
  • 9Lawrence Berkeley National Laboratory[EB/OL].URL:http://ita.ee.lbl.gov/,1997.
  • 10Computer Science Department,University of California,Berkeley[EB/OL].URL:http://www.cs.berkeley.edu/logs/,2002.

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