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  • 标题:Mining Users' Similarity from Moving Trajectories for Mobile E-commerce Recommendation
  • 本地全文:下载
  • 作者:Haidong Zhong ; Shaozhong Zhang ; Yanling Wang
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2014
  • 卷号:7
  • 期号:4
  • 页码:309-320
  • DOI:10.14257/ijhit.2014.7.4.26
  • 出版社:SERSC
  • 摘要:Users' similarity mining in mobile e-commerce systems is an important field with wide applications, such as personalized recommendation and accurate advertising. Moving trajectories of e-commerce users contain much useful information, providing a very good opportunity for understanding the users' interesting and discovering the similarity between mobile-device-holders. In this paper, we explores the problems in the existing mobile e- commerce recommendation methods, and propose a mobile users' moving trajectories mining based user similarity discovering approach for mobile e-commerce system. We formally defines the moving trajectory and view the areas, where users stay within for a certain time, as interested regions, which reflect the preferences of mobile-device-holders. Based on the number of overlapped interested areas, a user similarity measure method is proposed. Experimental evaluation, conducted based on the publicly available datasets commendably demonstrate the effectiveness of our approach.
  • 关键词:Users' similarity mining; Moving trajectories; Mobile e-commerce; ; Recommendation
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