GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Deterministic annealing EM algorithm
Neural Networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
SWAMI (poster session): a framework for collaborative filtering algorithm development and evaluation
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Latent Class Models for Collaborative Filtering
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Statistical Models for Co-occurrence Data
Statistical Models for Co-occurrence Data
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Toward case-based preference elicitation: similarity measures on preference structures
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Preference-based graphic models for collaborative filtering
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Information Diffusion Approach to Cold-Start Problem
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Addressing cold-start problem in recommendation systems
Proceedings of the 2nd international conference on Ubiquitous information management and communication
Knowledge worker intranet behaviour and usability
International Journal of Business Intelligence and Data Mining
Probabilistic relevance ranking for collaborative filtering
Information Retrieval
Short communication: Recommendation based on rational inferences in collaborative filtering
Knowledge-Based Systems
Mean-Variance Analysis: A New Document Ranking Theory in Information Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Designing a Metamodel-Based Recommender System
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
MoviExplain: a recommender system with explanations
Proceedings of the third ACM conference on Recommender systems
Language Models of Collaborative Filtering
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Optimizing multiple objectives in collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
Modeling Social Annotation: A Bayesian Approach
ACM Transactions on Knowledge Discovery from Data (TKDD)
Latent subject-centered modeling of collaborative tagging: An application in social search
ACM Transactions on Management Information Systems (TMIS)
Social and behavioural media access
SBNMA '11 Proceedings of the 2011 ACM workshop on Social and behavioural networked media access
Pushing the boundaries of crowd-enabled databases with query-driven schema expansion
Proceedings of the VLDB Endowment
A latent model for collaborative filtering
International Journal of Approximate Reasoning
Feature enriched nonparametric bayesian co-clustering
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
A Mobile Service Recommendation System Using Multi-Criteria Ratings
International Journal of Interdisciplinary Telecommunications and Networking
Query-driven context aware recommendation
Proceedings of the 7th ACM conference on Recommender systems
Facing the cold start problem in recommender systems
Expert Systems with Applications: An International Journal
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Collaborative filtering is a general technique for exploiting the preference patterns of a group of users to predict the utility of items for a particular user. Three different components need to be modeled in a collaborative filtering problem: users, items, and ratings. Previous research on applying probabilistic models to collaborative filtering has shown promising results. However, there is a lack of systematic studies of different ways to model each of the three components and their interactions. In this paper, we conduct a broad and systematic study on different mixture models for collaborative filtering. We discuss general issues related to using a mixture model for collaborative filtering, and propose three properties that a graphical model is expected to satisfy. Using these properties, we thoroughly examine five different mixture models, including Bayesian Clustering (BC), Aspect Model (AM), Flexible Mixture Model (FMM), Joint Mixture Model (JMM), and the Decoupled Model (DM). We compare these models both analytically and experimentally. Experiments over two datasets of movie ratings under different configurations show that in general, whether a model satisfies the proposed properties tends to be correlated with its performance. In particular, the Decoupled Model, which satisfies all the three desired properties, outperforms the other mixture models as well as many other existing approaches for collaborative filtering. Our study shows that graphical models are powerful tools for modeling collaborative filtering, but careful design is necessary to achieve good performance.