Conversational Case-Based Reasoning
Applied Intelligence
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
ITR: A Case-Based Travel Advisory System
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Experiments in dynamic critiquing
Proceedings of the 10th international conference on Intelligent user interfaces
Advances in conversational case-based reasoning
The Knowledge Engineering Review
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
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
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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Eliminating previously recommended items in a critiquing dialogue prevents the user from navigating back to acceptable items she critiqued earlier in the dialogue. An equally serious problem if previous recommendations are not eliminated is that acceptable items may be unreachable by any sequence of critiques. Progressive critiquing solves this dilemma while also making it easier for users to recognize when none of the available items are acceptable. In this paper, we present theoretical and empirical results that demonstrate the benefits of a critiquing strategy in which the user gives priority to constraints that must be satisfied in a progressive critiquing dialogue. We also present a new version of progressive critiquing in which mixed-initiative relaxation of constraints introduced by user critiquing choices that depart from this strategy greatly reduces their impact on dialogue outcomes.