Differences between novice and experienced users in searching information on the World Wide Web
Journal of the American Society for Information Science - Special topic issue: individual differences in virtual environments
IEEE Transactions on Knowledge and Data Engineering
User Modeling and User-Adapted Interaction
A comparative user study on rating vs. personality quiz based preference elicitation methods
Proceedings of the 14th international conference on Intelligent user interfaces
Evaluating Interface Variants on Personality Acquisition for Recommender Systems
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Design and user issues in personality-based recommender systems
Proceedings of the fourth ACM conference on Recommender systems
Personalizing the theme park: psychometric profiling and physiological monitoring
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Enhancing collaborative filtering systems with personality information
Proceedings of the fifth ACM conference on Recommender systems
Evaluating recommender systems from the user's perspective: survey of the state of the art
User Modeling and User-Adapted Interaction
Explaining the user experience of recommender systems
User Modeling and User-Adapted Interaction
Personality-based recommender systems: an overview
Proceedings of the sixth ACM conference on Recommender systems
Developing culturally relevant design guidelines for encouraging healthy eating behavior
International Journal of Human-Computer Studies
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Our previous research indicates that using personality quizzes is a viable and promising way to build user profiles to recommend entertainment products Based on these findings, our current research further investigates the feasibility of using personality quizzes to build user profiles not only for an active user but also his or her friends We first propose a general method that infers users' music preferences in terms of their personalities Our in-depth user studies show that while active users perceive the recommended items to be more accurate for their friends, they enjoy more using personality quiz based recommenders for finding items for themselves Additionally, we explore if domain knowledge has an influence on users' perception of the system We found that novice users, who are less knowledgeable about music, generally appreciated more personality-based recommenders Finally, we propose some design issues for recommender systems using personality quizzes.