A NOVEL METHOD OF USER INTEREST DRIFT DETECTION ENGAGING IN INDIVIDUAL BACKGROUND FACTORS
College of business Administration Zhejianggongshang University, Hangzhou, China
Center for Studies of Modern Business, Zhejiang Gongshang University, Hangzhou, China
Personalized service tends to be an emerging challenge in the field of interest mining on e-commerce platform, the issues of which include how to integrate the user's individual background factor, to hiddenly attain portal user interest behaviour, and to mine interest drift pattern. According to user interest drift problem of personalized service in network, this paper explains the user interest through an integration of individual background factor, user behaviour and interest. Meanwhile, it recommends the fuzzy logic thought to explain its impact factor weights comprehensively in order to reflect the level of the user interest on theme. And, it establishes the Hidden semi-Markov Model via user browsing path to detect whether the interest is drifted or not. Finally, the method is proved to be accurate through the experiment analysis.