Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
作者: Bamshad MobasherHonghua DaiTao LuoMiki Nakagawa
作者单位: 1School of Computer Science, Telecommunication, and Information Systems, DePaul University
刊名: Data Mining and Knowledge Discovery, 2002, Vol.6 (1), pp.61-82
来源数据库: Springer Nature Journal
DOI: 10.1023/A:1013232803866
关键词: Web usage miningclusteringpersonalizationcollaborative filteringdata mining
原始语种摘要: Abstract(#br)Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these techniques, including reliance on subjective user ratings, lack of scalability, and poor performance in the face of high-dimensional and sparse data. However, the discovery of patterns from usage data by itself is not sufficient for performing the personalization tasks. The critical step is the effective derivation of good quality and useful (i.e., actionable) “aggregate usage profiles” from these patterns. In this paper we present and experimentally evaluate two techniques, based on clustering of user transactions and clustering of pageviews, in order to discover overlapping aggregate profiles that can...
全文获取路径: Springer Nature  (合作)
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影响因子:2.877 (2012)

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