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New Technology of Library and Information Service  2015, Vol. 31 Issue (3): 67-74    DOI: 10.11925/infotech.1003-3513.2015.03.09
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The Probing of E-commerce User Need States by Page Cluster Analysis ——An Empirical Study on Women's Clothes from Taobao.com
Zhang Wenjun, Wang Jun, Xu Shanchuan
Department of Information Management, Peking University, Beijing 100871, China
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Abstract  

[Objective] It's vital to detect the consumers' shopping needs in the e-commerce environment by mining clickstream logs so as to achieve effective shopping guidance. [Methods] This paper first marks page types that users visit in Taobao.com, then uses K-means cluster to analyse the visit session data. Two clustering indexes are used, that are page-type and page-complexity. [Results] Based on page types, the visit sessions are clustered to four user need states, including direct management, continuous searching, product browsing and information seeking. The four types are then categorized into nine detailed ones based on page complexity. [Limitations] The effectiveness of the user need state analysis needs to be further validated in real-world environment. [Conclusions] It is an effecitve and operable method to detect and denote the e-shopper's need states by clustering analysis of the visiting sessions.

Key wordsUser need state      E-commerce      E-shopping behavior      K-means clustering     
Received: 16 September 2014      Published: 16 April 2015
:  TP393  

Cite this article:

Zhang Wenjun, Wang Jun, Xu Shanchuan. The Probing of E-commerce User Need States by Page Cluster Analysis ——An Empirical Study on Women's Clothes from Taobao.com. New Technology of Library and Information Service, 2015, 31(3): 67-74.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2015.03.09     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2015/V31/I3/67

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