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基于Web日志的个性化搜索引擎模型的发现 被引量：6

Discover personalized search engine model by mining Web logs
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摘要 个性化搜索是指同样的关键字对不同的人返回其感兴趣的搜索结果。对于不同的用户个体,同样的关键字可能有不同含义,如关键字"apple"被爱好音乐的人士理解为Apple iPod,但也会被健康饮食的人士理解为apple fruit。每次用户搜索关键字的过程,都会被记录在网站服务器的后台日志中。通过若干挖掘算法,将Web原始日志信息进行用户识别,会话分组后,提取单一用户多次会话中的搜索关键字关联规则,为实现个性化搜索引擎提供参考。 The Web site visitors＇ search keywords was recorded in the Web server log files. Analyzing and exploring associations in the search keywords of single Web user could provide the personal search results. This paper discovered the single user search keywords association rule by using algorithm SUSKARD.
作者 鲍钰
机构地区 华东师范大学软件学院
出处 《计算机应用研究》 CSCD 北大核心 2009年第5期1806-1809,共4页 Application Research of Computers
基金 国家"973"计划资助项目(2005CB321904)
关键词 WEB日志 个性化搜索 单用户搜索关键字关联规则发现算法 Web logs personal Web search SUSKARD algorithm
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献9

  • 1AGRAWAL R, IMIELINSKI T, SWAMI A. Mining association rules between sets of items in large database[ C ]//Proc of ACM SIGMOD International Conference on Management of Data. Washington DC: [s. n. ] ,1993:207-216.
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二级参考文献6

  • 1[1]Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large database[C]. In: Proc. of the ACM SIGMOD Conference on Man agent of data, 1993,207-216.
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共引文献15

同被引文献67

引证文献6

二级引证文献51

计算机应用研究
2009年 第5期

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