Abstract
In the area of electronic commerce, the personalized goods recommendation system is a very important research issue that raises user satisfaction, and increases loyalty towards the content provider. For this, the correct analysis of user preferences is essential, and most existing researches use a purchase history or a wish list. However, due to the rapid development of information technologies, commerce has progressed from e-commerce to U(Ubiquitous)-commerce. In the ubiquitous environment, computing devices of various types, including the mobile device itself, exist in user space; in addition, a broad range of information related to user preferences is generated while using these devices. Hence, if the information is efficiently managed, a more effective recommendation strategy will be established. This paper proposes a multi-agent based U-commerce system to efficiently collect and manage diverse context information that can occur in the ubiquitous environment. Therefore, a more personalized recommendation, which is reflected by various user preferences, is possible. A prototype was implemented in order to evaluate the proposed system, then, through results, the existing recommendation method is compared and the effectiveness of the system is confirmed.
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Lee, S., Lee, E. (2007). A Collective User Preference Management System for U-Commerce. In: Ata, S., Hong, C.S. (eds) Managing Next Generation Networks and Services. APNOMS 2007. Lecture Notes in Computer Science, vol 4773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75476-3_3
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DOI: https://doi.org/10.1007/978-3-540-75476-3_3
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