GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Enriching buyers' experiences: the SmartClient approach
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Evaluating example-based search tools
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Human Problem Solving
Journal of Artificial Intelligence Research
Adaptive decision support system (ADSS) for B2C e-commerce
ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
Overcoming incomplete user models in recommendation systems via an ontology
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
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One crucial task for e-commerce systems is to help buyers find products that not only satisfy their preferences but also reduce their search effort. Usually the amount of available products is far beyond the upper limit that any individual could process by hand; thus product search tools are employed to generate target product (s) by eliciting the buyer's preferences and then executing some kind of choice strategies. We propose in this paper an extended effort-accuracy framework for measuring the performance of various choice strategies in terms of cognitive effort, elicitation effort and decision accuracy. The performance of a variety of basic choice strategies is further studied by theoretical analysis as well as empirical simulations. It shows that the performance of a given choice strategy is a tradeoff between choice accuracy and effort required from the users. The proposed framework also suggests a new efficient method of evaluating the user interfaces of e-commerce systems by analyzing the performance of the underlying choice strategies.