Information Retrieval
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
MPTrain: a mobile, music and physiology-based personal trainer
Proceedings of the 8th conference on Human-computer interaction with mobile devices and services
Introduction to Information Retrieval
Introduction to Information Retrieval
Social ranking: uncovering relevant content using tag-based recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Tag recommendations in social bookmarking systems
AI Communications
A Hybrid Recommender System for Context-aware Recommendations of Mobile Applications
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Context-Aware Recommendation by Aggregating User Context
CEC '09 Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing
ItemRank: a random-walk based scoring algorithm for recommender engines
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Music Playlist Recommendation Based on User Heartbeat and Music Preference
ICCTD '09 Proceedings of the 2009 International Conference on Computer Technology and Development - Volume 01
Music Recommendation Using Content and Context Information Mining
IEEE Intelligent Systems
Context awareness by case-based reasoning in a music recommendation system
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
International Journal of Approximate Reasoning
Affectively intelligent and adaptive car interfaces
Information Sciences: an International Journal
Mining mood-specific movie similarity with matrix factorization for context-aware recommendation
Proceedings of the Workshop on Context-Aware Movie Recommendation
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
EMIR: a novel music retrieval system for mobile devices incorporating analysis of user emotion
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Detecting stress during real-world driving tasks using physiological sensors
IEEE Transactions on Intelligent Transportation Systems
Towards personalized context-aware recommendation by mining context logs through topic models
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
MusicalHeart: a hearty way of listening to music
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
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Recommender systems are powerful tools that support the user in their quest to find the multimedia they are looking for. Such systems present multimedia contents or provide recommendations by taking into consideration two dimensions of inputs: content (item), and user (consumer). Little attention has been paid to increasing the quality of the experience by understanding the contextual aspect of the user when he/she wants to consume multimedia content. By including user's biological signal and leveraging collaborative filtering, we can build a context-aware model that establish the bridge between the multimedia content, and the user's context containing physiological parameters. Hence, the proposed model finds the latent preferences of users in a given context from other similar users. The model also finds the latent items consumed in a given context from other similar items. We then map context-based items for a particular user to find most relevant items in that context. Our experimental results have shown the feasibility to personalize the recommendation according to the user's context.