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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/27366


    Title: A Personalized and Integrative Comparison Shopping Engine and Its Applications
    Authors: 苑守慈
    Yuan,Soe-Tsyr
    Keywords: (Multi-) agent systems;Comparison shopping;Reinforcement learning;Neural networks;Consumer valuation models
    Date: 2003-01
    Issue Date: 2009-01-17 16:35:46 (UTC+8)
    Abstract: Agents are the catalysts for commerce on the Web today. For example, comparison-shopping agents mediate the interactions between consumers and suppliers in order to yield markets that are more efficient. However, today`s shopping agents are price-dominated, unreflective of the nature of supplier/consumer differentiation or the changing course of differentiation over time. This paper aims to tackle this dilemma and advances shopping agents into a stage where both kinds of differentiation are taken into account for enhanced understanding of the realities. We call them personalized and integrative shopping agents. These agents can leverage the interactive power of the Web for a more accurate understanding of consumer`s preferences. This paper then presents a comparison-shopping engine that can be easily instantiated to become personalized and integrative shopping agents. This engine comprises of a product/merchant information collector, a consumer behavior extractor, a user profile manager, and an on-line learning personalized ranking module. We have built this engine and instantiated a comparison-shopping system for collecting preliminary evaluation results. The results show that this system is quite promising in overcoming the reality challenges of comparison shopping. In order to strengthen the contributions of this engine, we also gave a fielded application of this engine for personalized travel information discovery and explained the great potentials of this engine for a variety of comparison-shopping tasks.
    Relation: Decision Support Systems, 34(2), 139-156
    Data Type: article
    DOI link: http://dx.doi.org/10.1016/S0167-9236(02)00077-5
    DOI: 10.1016/S0167-9236(02)00077-5
    Appears in Collections:[Department of MIS] Periodical Articles

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