ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
Being accurate is not enough: how accuracy metrics have hurt recommender systems
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Acceptance issues of personality-based recommender systems
Proceedings of the third ACM conference on Recommender systems
Tutorial on evaluating recommender systems
Proceedings of the fourth ACM conference on Recommender systems
Novelty and Diversity in Top-N Recommendation -- Analysis and Evaluation
ACM Transactions on Internet Technology (TOIT)
Using personality to adjust diversity in recommender systems
Proceedings of the 24th ACM Conference on Hypertext and Social Media
Human Decision Making and Recommender Systems
ACM Transactions on Interactive Intelligent Systems (TiiS)
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The existing approaches for enhancing diversity in online recommendations neglect the user's spontaneous needs that might be potentially influenced by her/his personality. In this paper, we report our ongoing research on exploring the actual impact of personality values on users' needs for recommendation diversity. The results from a preliminary user survey are reported, that show the significantly causal relationship from personality factors (such as conscientiousness) to the users' diversity preference (not only over the item's individual attributes but also on all attributes when they are combined). We further present our plan for the follow-up work and discuss its practical implications.