论文信息 - USING CONTEXTUAL CONDITIONAL PREFERENCES FOR RECOMMENDATION TASKS: A CASE STUDY IN THE MOVIE DOMAIN

USING CONTEXTUAL CONDITIONAL PREFERENCES FOR RECOMMENDATION TASKS: A CASE STUDY IN THE MOVIE DOMAIN

Recommendation engines aim to propose users items they are interested in by looking at the user interaction with a system. However, individual interests may be drastically influenced by the context in which decisions are taken. We present an attempt to model user interests via a set of contextual conditional preferences. We show that usage of proposed preferences gives reasonable values of the accuracy and the precision even when the dataset is quite small.

[1] Kinshuk,et al. A Rule-Based Recommender System to Suggest Learning Tasks , 2014, Intelligent Tutoring Systems.

[2] Jadzia Cendrowska,et al. PRISM: An Algorithm for Inducing Modular Rules , 1987, Int. J. Man Mach. Stud..

[3] Robin Burke,et al. Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models , 2015, RecSys.

[4] Gerhard Friedrich,et al. Recommender Systems: Knowledge-based recommendation , 2010 .

[5] Francesco Ricci,et al. Context-Aware Recommender Systems , 2011, AI Mag..

[6] Barry Smyth,et al. Case-Based Recommendation , 2007, The Adaptive Web.

[7] Ricardo Dias,et al. Improving Music Recommendation in Session-Based Collaborative Filtering by Using Temporal Context , 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

[8] Marko Tkalcic,et al. Database for contextual personalization , 2011 .

[9] Evaggelia Pitoura,et al. A context-aware preference database system , 2008, Int. J. Pervasive Comput. Commun..

[10] Ronen I. Brafman,et al. CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements , 2011, J. Artif. Intell. Res..