Evaluating compound critiquing recommenders

James Reilly, Jiyong Zhang, Lorraine McGinty, Pearl Pu, Barry Smyth
2007 Proceedings of the 8th ACM conference on Electronic commerce - EC '07  
Conversational recommender systems are designed to help users to more efficiently navigate complex product spaces by alternatively making recommendations and inviting users' feedback. Compound critiquing techniques provide an efficient way for users to feed back their preferences (in terms of several simultaneous product attributes) when interfacing with conversational recommender systems. For example, in the laptop domain a user might wish to express a preference for a laptop that is Cheaper,
more » ... ighter, with a Larger Screen. While recently a number of techniques for dynamically generating compound critiques have been proposed, to date there has been a lack of direct comparison of these approaches in a real-user study. In this paper we will compare two alternative approaches to the dynamic generation of compound critiques based on ideas from data mining and multi-attribute utility theory. We will demonstrate how both approaches support users to more efficiently navigate complex product spaces highlighting, in particular, the influence of product complexity and interface strategy on recommendation performance and user satisfaction.
doi:10.1145/1250910.1250929 dblp:conf/sigecom/ReillyZMPS07 fatcat:ucd2bcpnjjasdoavionuxkrokq