ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Diverse Product Recommendations Using an Expressive Language for Case Retrieval
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Understanding and improving automated collaborative filtering systems
Understanding and improving automated collaborative filtering systems
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
On the role of diversity in conversational recommender systems
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Distributed collaborative filtering with domain specialization
Proceedings of the 2007 ACM conference on Recommender systems
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Qualitative vs. quantitative plan diversity in case-based planning
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
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Conversational recommender systems adapt the sets of products they recommend in light of user feedback. Our contribution here is to devise and compare four different mechanisms for enhancing the diversity of the recommendations made by collaborative recommenders. Significantly, we increase diversity using collaborative data only. We find that measuring the distance between products using Hamming Distance is more effective than using Inverse Pearson Correlation.