Interactive Critiquing forCatalog Navigation in E-Commerce
Artificial Intelligence Review
Evaluating example-based search tools
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
VISCORS: A Visual-Content Recommender for the Mobile Web
IEEE Intelligent Systems
Integrating tradeoff support in product search tools for e-commerce sites
Proceedings of the 6th ACM conference on Electronic commerce
Multimedia-based interactive advising technology for online consumer decision support
Communications of the ACM - Special issue: RFID
Case-based recommender systems
The Knowledge Engineering Review
Enhancing Mobile Web Access Using Intelligent Recommendations
IEEE Intelligent Systems
Supporting Context-Aware Media Recommendations for Smart Phones
IEEE Pervasive Computing
Acquiring and Revising Preferences in a Critique-Based Mobile Recommender System
IEEE Intelligent Systems
International Journal of Electronic Commerce
Preference-Based Organization Interfaces: Aiding User Critiques in Recommender Systems
UM '07 Proceedings of the 11th international conference on User Modeling
A personalized system for conversational recommendations
Journal of Artificial Intelligence Research
ExpertClerk: navigating shoppers' buying process with the combination of asking and proposing
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A live-user evaluation of incremental dynamic critiquing
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Long-term and session-specific user preferences in a mobile recommender system
Proceedings of the 13th international conference on Intelligent user interfaces
Conversational Case-Based Recommendations Exploiting a Structured Case Model
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
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Supporting conversational approaches in mobile recommender systems is challenging because of the inherent limitations of mobile devices and the dependence of produced recommendations on the context. In a previous work, we proposed a critique-based mobile recommendation approach and presented the results of a live users evaluation. Live-user evaluations are expensive and there we could not compare different system variants to check all our research hypotheses. In this paper, we present an innovative simulation methodology and its use in the comparison of different user-query representation approaches. Our simulation test procedure replays off-line, against different system variants, interactions recorded in the live-user evaluation. The results of the simulation tests show that the composite query representation, which employs both logical and similarity queries, does improve the recommendation performance over a representation using either a logical or a similarity query.