User and Context Information in Context-Aware Recommender Systems: A Systematic Literature Review

Using contextual information inside recommendation systems is an effective approach to generate more accurate recommendations. This paper present a review conducted to identify what user’s and context’s information it’s considered relevant by researchers to generate contextual recommendations from 2012 to 2015, based on Kitchenham systematic literature review methodology. The results indicated that there is a large set of possible user’s and context’s information that can be used to do recommendations. This review can be taken as basis for future context-aware recommender systems development, as well as development of contextual user models.

[1]  Markus Schedl,et al.  Ameliorating Music Recommendation: Integrating Music Content, Music Context, and User Context for Improved Music Retrieval and Recommendation , 2013, MoMM '13.

[2]  Zhiting Hu,et al.  Dynamic User Modeling in Social Media Systems , 2015, TOIS.

[3]  Bernd Ludwig,et al.  Context relevance assessment and exploitation in mobile recommender systems , 2012, Personal and Ubiquitous Computing.

[4]  Lior Rokach,et al.  Recommender Systems Handbook , 2010 .

[5]  Francesco Ricci,et al.  Contextual music information retrieval and recommendation: State of the art and challenges , 2012, Comput. Sci. Rev..

[6]  Shlomo Berkovsky Ubiquitous User Modeling in Recommender Systems , 2005, User Modeling.

[7]  Seyed Reza Shahamiri,et al.  A systematic review of scholar context-aware recommender systems , 2015, Expert Syst. Appl..

[8]  Francesco Ricci,et al.  Distributional semantic pre-filtering in context-aware recommender systems , 2015, User Modeling and User-Adapted Interaction.

[9]  Jörg Schreck,et al.  Security and Privacy in User Modeling , 2003, Human-Computer Interaction Series.

[10]  Maurice D. Mulvenna,et al.  Personalization on the Net using Web mining: introduction , 2000, CACM.

[11]  Pattie Maes,et al.  Agents that reduce work and information overload , 1994, CACM.

[12]  Wei-Po Lee,et al.  Making smartphone service recommendations by predicting users' intentions: A context-aware approach , 2014, Inf. Sci..

[13]  Tim Hussein,et al.  Hybreed: A software framework for developing context-aware hybrid recommender systems , 2012, User Modeling and User-Adapted Interaction.

[14]  Pearl Brereton,et al.  Systematic literature reviews in software engineering - A systematic literature review , 2009, Inf. Softw. Technol..

[15]  Maria Fasli,et al.  Utilizing contextual ontological user profiles for personalized recommendations , 2014, Expert Syst. Appl..

[16]  Abayomi Moradeyo Otebolaku,et al.  Context-aware media recommendations for smart devices , 2014, J. Ambient Intell. Humaniz. Comput..

[17]  Erik Duval,et al.  Context-Aware Recommender Systems for Learning: A Survey and Future Challenges , 2012, IEEE Transactions on Learning Technologies.

[18]  Li Chen,et al.  Emotional States Associated with Music , 2015, ACM Trans. Interact. Intell. Syst..

[19]  Li Chen,et al.  Augmenting service recommender systems by incorporating contextual opinions from user reviews , 2015, User Modeling and User-Adapted Interaction.

[20]  Dietmar Jannach,et al.  Preface to the special issue on context-aware recommender systems , 2013, User Modeling and User-Adapted Interaction.

[21]  Andreas Stafylopatis,et al.  Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments , 2013, 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization.

[22]  Tsvi Kuflik,et al.  Mediation of user models for enhanced personalization in recommender systems , 2007, User Modeling and User-Adapted Interaction.

[23]  Kyung-Yong Chung,et al.  Item recommendation based on context-aware model for personalized u-healthcare service , 2011, Multimedia Tools and Applications.

[24]  Xing Xie,et al.  Adaptive content recommendation for mobile users: Ordering recommendations using a hierarchical context model with granularity , 2014, Pervasive Mob. Comput..

[25]  Luis Oliva,et al.  Context-Aware User Modeling Strategies for Journey Plan Recommendation , 2015, UMAP.

[26]  Alexis Tsoukiàs,et al.  Multicriteria User Modeling in Recommender Systems , 2011, IEEE Intelligent Systems.

[27]  Patty Kostkova,et al.  Modeling User Preferences in Recommender Systems , 2014, ACM Trans. Interact. Intell. Syst..

[28]  Bernd Ludwig,et al.  You Are What You Eat: Learning User Tastes for Rating Prediction , 2013, SPIRE.

[29]  Iván Cantador,et al.  Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols , 2013, User Modeling and User-Adapted Interaction.

[30]  Fan Yang,et al.  Modeling and broadening temporal user interest in personalized news recommendation , 2014, Expert Syst. Appl..

[31]  Kee-Sung Lee,et al.  Collaborative user modeling for enhanced content filtering in recommender systems , 2011, Decis. Support Syst..

[32]  M. Shamim Hossain,et al.  Towards context-sensitive collaborative media recommender system , 2014, Multimedia Tools and Applications.

[33]  Ivica Crnkovic,et al.  A systematic review of software architecture evolution research , 2012, Inf. Softw. Technol..

[34]  Alda Lopes Gançarski,et al.  Following the User's Interests in Mobile Context-Aware Recommender Systems: The Hybrid-e-greedy Algorithm , 2012, 2012 26th International Conference on Advanced Information Networking and Applications Workshops.

[35]  Chris D. Nugent,et al.  Ontological User Profile Modeling for Context-Aware Application Personalization , 2012, UCAmI.

[36]  Dominik Heckmann,et al.  Ubiquitous user modeling , 2006 .

[37]  Toon De Pessemier,et al.  A user-centric evaluation of context-aware recommendations for a mobile news service , 2016, Multimedia Tools and Applications.

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

[39]  Abayomi Moradeyo Otebolaku,et al.  Context-Aware Media Recommendations , 2014, 2014 28th International Conference on Advanced Information Networking and Applications Workshops.

[40]  Boris Brandherm,et al.  Gumo - The General User Model Ontology , 2005, User Modeling.

[41]  Rafael Valencia-García,et al.  RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes , 2015, Expert Syst. Appl..

[42]  Samee Ullah Khan,et al.  A survey on context-aware recommender systems based on computational intelligence techniques , 2015, Computing.