Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Predictive Statistical Models for User Modeling
User Modeling and User-Adapted Interaction
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
The SACSO methodology for troubleshooting complex systems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
IEEE Transactions on Knowledge and Data Engineering
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part IV
The impact of recommender systems on item-, user-, and rating-diversity
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
The relation between user intervention and user satisfaction for information recommendation
Proceedings of the 27th Annual ACM Symposium on Applied Computing
User Modeling and User-Adapted Interaction
Urban point-of-interest recommendation by mining user check-in behaviors
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
Like-Minded communities: bringing the familiarity and similarity together
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
International Journal of Systems and Service-Oriented Engineering
You are what you consume: a bayesian method for personalized recommendations
Proceedings of the 7th ACM conference on Recommender systems
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This paper proposes a novel approach for constructing users' movie preference models using Bayesian networks. The advantages of the constructed preference models are 1) consideration of users' context in addition to users' personality, 2) multiple applications, such as recommendation and promotion. Data acquisition process through a WWW questionnaire survey and a Bayesian network model construction process using the data are described. The effectiveness of the constructed model in terms of recommendation and promotion is also demonstrated through experiments.