The FindMe Approach to Assisted Browsing
IEEE Expert: Intelligent Systems and Their Applications
Evaluating example-based search tools
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Artificial Intelligence Review
ACM Transactions on Computer-Human Interaction (TOCHI)
Evaluating compound critiquing recommenders: a real-user study
Proceedings of the 8th ACM conference on Electronic commerce
Constraint-based recommender systems: technologies and research issues
Proceedings of the 10th international conference on Electronic commerce
Evaluating critiquing-based recommender agents
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A personalized system for conversational recommendations
Journal of Artificial Intelligence Research
The ins and outs of critiquing
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Knowledge-Based Systems
Knowledge-based navigation of complex information spaces
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A comparative study of compound critique generation in conversational recommender systems
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Experience-Based critiquing: reusing critiquing experiences to improve conversational recommendation
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Critiquing-based recommenders: survey and emerging trends
User Modeling and User-Adapted Interaction
Improving the performance of unit critiquing
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
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In contrast to search-based approaches, critiquing-based recommender systems provide a navigation-based interface where users are enabled to critique displayed recommendations as a means of preference elicitation. In this paper we present Recomment, our approach to natural language based unit critiquing. We discuss the developed prototype and present the corresponding user interface. In order to show the applicability of our concepts, we present the results of a user study. This study shows that speech interfaces have the potential to improve the perceived ease of use as well as the overall quality of recommendations.