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基于时效性的Web页面个性化推荐模型的研究 被引量：6

Web Pageviews for Personalized Recommendation Model Based on Time-validity
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摘要 Internet的快速增长导致了对个性化服务需求急剧增加。该文通过分析个性化挖掘的特点,提出了基于时效性的Web页面个性化推荐模型。该模型的挖掘算法在FP-Tree的存储结构上加入时效价值系数,并进行增量挖掘。通过实验证明,该模型挖掘出来的信息,能够更好地符合用户的真实需求。 The idea of time-validity is proposed based on the analysis of characteristics of Web pageviews association rules for personalized recommendation. A model of mining association rules for personalized recommendation. A new interest-measure called time-validity for rules is based on this model, which allows for increasable mining and supports more user-interaction in the optimized rule-mining process.
作者 沈云斐 沈国强 蒋丽华 覃征
机构地区 清华大学软件学院
出处 《计算机工程》 EI CAS CSCD 北大核心 2006年第13期80-81,99,共3页 Computer Engineering
基金 国家"863"计划基金资助项目"MES为基础的数字油田基础研究"(2003AA412020)
关键词 WEB挖掘 个性化推荐模型 时效性 Web mining Personalization recommendation model Time-validity
分类号 TP391.4 [自动化与计算机技术—计算机应用技术]
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参考文献12

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二级参考文献20

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共引文献20

同被引文献44

引证文献6

二级引证文献24

计算机工程
2006年 第13期

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