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Received:September 28, 2013 Revised:October 15, 2013
Received:September 28, 2013 Revised:October 15, 2013
中文摘要: 点击流数据是分析互联网用户心理倾向的关键,互联网用户的聚类可以通过分析点击流数据实现. 本文提出了一种基于向量的相似度计算方法,将点击流数据转化为向量数据. 通过对向量的计算来得出聚类的结果. 算法克服了传统的聚类算法的一些缺点,更能符合研究人员研究Web点击流数据时关于个性化聚类的要求.
Abstract:Clickstream data are the key to analysis the psychological tendency of Internet users. Internet users clustering can be realized by analyzing the clickstream data.This paper presents a similarity calculation method based on vector. Clickstream data can be converted to vector data.Through the calculation of vector clustering, results could be obtained. Algorithm overcomes the drawbacks of the traditional clustering algorithm. It can meet researchers study of web clickstream data about the requirements of personalized clustering more.
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徐昊,谢文阁.基于向量的点击流聚类算法.计算机系统应用,2014,23(5):158-161
XU Hao,XIE Wen-Ge.Clickstream Clustering Algorithm Baced on Vector.COMPUTER SYSTEMS APPLICATIONS,2014,23(5):158-161
徐昊,谢文阁.基于向量的点击流聚类算法.计算机系统应用,2014,23(5):158-161
XU Hao,XIE Wen-Ge.Clickstream Clustering Algorithm Baced on Vector.COMPUTER SYSTEMS APPLICATIONS,2014,23(5):158-161