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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (2): 74-85    DOI: 10.11925/infotech.2096-3467.2017.0886
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Identifying User Interests Based on Browsing Behaviors
Hongwei Liu1,Hongming Gao1,Li Chen2(),Mingjun Zhan1,Zhouyang Liang1
1(School of Management, Guangdong University of Technology, Guangzhou 510520, China)
2(Guangdong Youth Vocational College, Guangzhou 510507, China)
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Abstract  

[Objective] This paper proposes a model to identify the interests of online shoppers based on their browsing behaviors, aiming to improve the personalized recommendation services. [Methods] First, we launched experiment to collect clickstream data from Taobao and TMall. Second, we used the Bisecting K-means algorithm to analyze the retrieved data. Finally, we established the relationship mapping structure between interests and behaviors. [Results] We found four types of user’s implicit interests: Attention, Comprehension, Attitudes and Intention. Users with the Attitude and Intention types tended to make purchase. The characteristics of browsing paths were different among the users. [Limitations] We did not examine unstructured data, i.e., online sales advertisements, in this study. [Conclusions] This paper investigates the user interests in online shopping, and then improve the personalized recommendation services of the E-commerce platforms.

Key wordsImplicit Interest      Clickstream      Bisecting K-means Algorithm     
Received: 01 September 2017      Published: 07 March 2018

Cite this article:

Hongwei Liu,Hongming Gao,Li Chen,Mingjun Zhan,Zhouyang Liang. Identifying User Interests Based on Browsing Behaviors. Data Analysis and Knowledge Discovery, 2018, 2(2): 74-85.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.0886     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I2/74

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