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ABSTRACT
<p>Shopping online is still confusing owing to the vast number of vendors, inconsistent information, and different vendor site organization. Shopping agents based on user-centered business models have been unsuccessful because shoppers have not perceived price comparison as a service worth paying for. So, shopping bots today are biased in favor of vendors who pay fees to be listed. To make user-centered business models viable, shopping agents must become more useful. To this end, we developed IntelliShopper, a shopping assistant that can learn shoppers' heterogeneous and dynamic preferences by observing their behavior unobtrusively. IntelliShopper can also present shoppers with customized information about new items it discovers by autonomously monitoring vendor sites.</p>
INDEX TERMS
E-shopping, adaptive assistant, customization, persona, learning, relevance feedback, autonomous monitoring, privacy, IntelliShopper
CITATION
Alvaro E. Monge, Filippo Menczer, W. Nick Street, "Adaptive Assistants for Customized E-Shopping", IEEE Intelligent Systems, vol. 17, no. , pp. 12-19, November/December 2002, doi:10.1109/MIS.2002.1134357
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