Title: User-based collaborative filtering recommendation method combining with privacy concerns intensity in mobile commerce

Authors: Qibei Lu; Feipeng Guo; Ruoyi Zhang

Addresses: School of Cross-Border E-Commerce, Zhejiang International Studies University, Hangzhou 310012, Zhejiang Province, China; School of Science and Technology, Zhejiang International Studies University, Hangzhou 310012, Zhejiang Province, China ' Modern Business Research Centre, Zhejiang Gongshang University, Hangzhou 310012, Zhejiang Province, China; Information Technology Department, Zhejiang Institute of Economics and Trade, Hangzhou 310012, Zhejiang Province, China ' College of Business, City University of Hong Kong, Kowloon Tong, Hong Kong, China

Abstract: The existing personalised recommender system gives little consideration to users' privacy concerns in mobile commerce. In order to address this issue and some other shortcomings in item recommendations, the paper proposes a novel user-based collaborative filtering recommendation method combining with privacy concerns intensity and introduces the users' six dimensions privacy concerns factors, such as privacy tendency, internal control point, openness, extroversion, agreeableness, and social group influence. The paper puts forward the metric method of privacy concerns intensity with these privacy concerns influence factors, which are used to obtain the similarity preference of users for collective filtering recommendation. Experiments show that this method has more advantages than other algorithms. More importantly, a combination of subjective privacy concerns and objective recommendation technology can reduce the influence of users' privacy concerns on their acceptance of mobile personalised service.

Keywords: influence factors of privacy concerns; privacy concerns intensity; online user's preference; collective filtering; personalised recommendation.

DOI: 10.1504/IJWMC.2019.101028

International Journal of Wireless and Mobile Computing, 2019 Vol.17 No.1, pp.63 - 70

Received: 04 Oct 2018
Accepted: 07 Feb 2019
Published online: 22 Jul 2019 *

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