Fast discovery of association rules
Advances in knowledge discovery and data mining
Interactive Critiquing forCatalog Navigation in E-Commerce
Artificial Intelligence Review
The FindMe Approach to Assisted Browsing
IEEE Expert: Intelligent Systems and Their Applications
Comparison-Based Recommendation
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
An evaluation of the usefulness of case-based explanation
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
On the role of diversity in conversational recommender systems
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Knowledge-based navigation of complex information spaces
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Artificial Intelligence Review
Generating Diverse Compound Critiques
Artificial Intelligence Review
On the role of trust in collaborative Web search
Artificial Intelligence Review
Evaluating product search and recommender systems for E-commerce environments
Electronic Commerce Research
Constraint-based recommender systems: technologies and research issues
Proceedings of the 10th international conference on Electronic commerce
Mood and Recommendations: On Non-cognitive Mood Inducers for High Quality Recommendation
APCHI '08 Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction
Techniques for fast query relaxation in content-based recommender systems
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
WISE'07 Proceedings of the 8th international conference on Web information systems engineering
Intelligent tagging interfaces: beyond folksonomy
UIST '10 Adjunct proceedings of the 23nd annual ACM symposium on User interface software and technology
Proceedings of the 16th international conference on Intelligent user interfaces
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
Customer relationship management and Web mining: the next frontier
Data Mining and Knowledge Discovery
The Tag Genome: Encoding Community Knowledge to Support Novel Interaction
ACM Transactions on Interactive Intelligent Systems (TiiS) - Special Issue on Common Sense for Interactive Systems
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Recommender systems bring together ideas from information retrieval and filtering, user profiling, adaptive interfaces and machine learning in an attempt to offer users more personalized and responsive search systems. Conversational recommenders guide a user through a sequence of iterations, suggesting specific items, and using feedback from users to refine their suggestions in subsequent iterations. Different recommender systems look for different types of feedback from users. In this paper we examine the role of critiquing, a form of feedback in which the user indicates a preference over a particular feature of a recommended item. For example, when shopping for a PC a user might indicate that they like the current suggestion but they are looking for something "cheaper"; "cheaper" is a critique over the price feature of the PC case. Sometimes it is useful to critique multiple features simultaneously (compound critiques). In this paper we describe how a recommender can automatically discover useful compound critiques during the recommendation session and how these critiques can be used to improve recommendation efficiency.