Proceedings of the ECAI 2006 Workshop on Recommender Systems in conjunction with the 17 th European Conference on Artificial Intelligence
نویسندگان
چکیده
Knowledge-based recommender technologies pro-vide a couple of mechanisms for improving the accessibility ofproduct assortments for customers, e.g., in situations whereno solution can be found for a given set of customer require-ments, the recommender application calculates a set of repairactions which can guarantee the identification of a solution.Further examples for such mechanisms are explanations orproduct comparisons. All these mechanisms have a certaineffect on the behavior of customers interacting with a rec-ommender application. In this paper we present results froma user study, which focused on the analysis of effects of dif-ferent recommendation mechanisms on the overall customeracceptance of recommender technologies.
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