A User Adaptive Mobile Commerce System with a Middlet Application
Mobile Commerce (MC) has some common critical problems such as constraints on small mobile device, expensive charge system, limited contents, and so on. In this paper we propose some solutions for solving the problems as follows: 1) personalized contents providing to increase the usability of the device by reducing the amount of information transferred to the device with personalization policy. 2) A middlet application to support user’s purchase activities such as products searching, ordering and settlement on the device with a minimum network connection. The solutions make us to overcome the both problems of the device with small screen and memory and expensive charge system.
KeywordsMobile Device Association Rule Recommender System Minimum Support Apriori Algorithm
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- 5.Thorsteinn, S., “Lecture Note: Self-Organizing Algorithms”, http://www.hh.se/staff/denni
- 6.IBM Almaden Research Center, “Mining Sequential Patterns” http://www.cs.duke.edu/~geng/
- 7.Purdom, P., Gucht, D.V., Average Case Performance of the Apriori Algorithm Technica reports from Indiana University Computer Science DepartmentGoogle Scholar
- 8.Tveit, A., Peer-to-peer based recommendations for mobile commerce. Proceedings of th first inter-national workshop on Mobile commerce July 2001Google Scholar