Abstract
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.
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References
Maes, P., Others: Agents that reduce work and information overload. Communications of the ACM 37(7) (1994) 30–40
Jawaheer, G., Weller, P., Kostkova, P.: Modeling User Preferences in Recommender Systems. ACM Transactions on Interactive Intelligent Systems 4(2) (2014) 1–26
Mulvenna, M.D., Anand, S.S., Büchner, A.G.: Personalization on the Net using Web mining: introduction. Communications of the ACM 43(8) (2000) 122–125
Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. Recommender systems handbook (2011) 67–80
Baltrunas, L., Ludwig, B., Peer, S., Ricci, F.: Context relevance assessment and exploitation in mobile recommender systems. Personal and Ubiquitous Computing 16(5) (2012) 507–526
Codina, V., Mena, J., Oliva, L.: Context-Aware User Modeling Strategies for Journey Plan Recommendation. In: User Modeling, Adaptation and Personalization. Springer (2015) 68–79
Berkovsky, S.: Ubiquitous User Modeling in Recommender Systems. Um 2005 (2005) 496–498
Lakiotaki, K., Matsatsinis, N.F., Tsoukiàs, A.: Multicriteria user modeling in recommender systems. IEEE Intelligent Systems 26 (2011) 64–76
Schreck, J.: Security and Privacy in User Modeling. Number September. (2003)
Siolas, G., Caridakis, G., Mylonas, P., Kollias, S., Stafylopatis, A.: Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments. 2013 8th International Workshop on Semantic and Social Media Adaptation and Personalization (December 2013) 27–32
Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. Recommender systems handbook (2011) 67–80
Berkovsky, S., Kuflik, T., Ricci, F.: Mediation of user models for enhanced personalization in recommender systems. User Modelling and User-Adapted Interaction 18(3) (2008) 245–286
Kim, H.N., Ha, I., Lee, K.S., Jo, G.S., El-Saddik, A.: Collaborative user modeling for enhanced content filtering in recommender systems. Decision Support Systems 51(4) (2011) 772–781
Ricci, F., Rokach, L., Shapira, B., Kantor, P.B.: Recommender Systems Handbook. Springer US, Boston, MA (2011)
Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., Linkman, S.: Systematic literature reviews in software engineering - A systematic literature review. Information and Software Technology 51(1) (2009) 7–15
Breivold, H.P., Crnkovic, I., Larsson, M.: A systematic review of software architecture evolution research. Inf. Softw. Technol. 54(1) (2012) 16–40
Champiri, Z.D., Shahamiri, S.R., Salim, S.S.B.: A systematic review of scholar context-aware recommender systems. Expert Systems with Applications 42(3) (September 2014) 1743–1758
Adomavicius, G., Jannach, D.: Preface to the special issue on context-aware recommender systems. User Modeling and User-Adapted Interaction 24(1-2) (2014) 1–5
Abbas, A., Zhang, L., Khan, S.U.: A survey on context-aware recommender systems based on computational intelligence techniques. Computing (2015)
De Pessemier, T., Courtois, C., Vanhecke, K., Van Damme, K., Martens, L., De Marez, L.: A user-centric evaluation of context-aware recommendations for a mobile news service. Multimedia Tools and Applications (2015)
Han, J., Schmidtke, H.R., Xie, X., Woo, W.: Adaptive content recommendation for mobile users: Ordering recommendations using a hierarchical context model with granularity. Pervasive and Mobile Computing 13 (2014) 85–98
Schedl, M.: Ameliorating Music Recommendation: Integrating Music Content, Music Context, and User Context for Improved Music Retrieval and Recommendation. Proceedings of International Conference on Advances in Mobile Computing & Multimedia (2013) 3:3—3:9
Chen, G., Chen, L.: Augmenting service recommender systems by incorporating contextual opinions from user reviews. User Modeling and User-Adapted Interaction (2015)
Otebolaku, A.M., Andrade, M.T.: Context-aware media recommendations. Proceedings - 2014 IEEE 28th International Conference on Advanced Information Networking and Applications Workshops, IEEE WAINA 2014 1 (2014) 191–196
Otebolaku, A.M., Andrade, M.T.: Context-aware media recommendations for smart devices. Journal of Ambient Intelligence and Humanized Computing 6(1) (2014) 13–36
Kaminskas, M., Ricci, F.: Contextual music information retrieval and recommendation: State of the art and challenges. Computer Science Review 6(2-3) (2012) 89–119
Deng, J.J., Leung, C.H.C., Milani, A., Chen, L.I.: Emotional States Associated with Music : Classification, Prediction of Changes, and Consideration in Recommendation. 5(1) (2015)
Codina, V., Ricci, F., Ceccaroni, L.: Distributional semantic pre-filtering in context-aware recommender systems. User Modeling and User-Adapted Interaction (2015)
Yin, H., Cui, B.I.N., Chen, L., Hu, Z., Zhou, X.: Dynamic User Modeling in Social Media Systems. 33(3) (2015)
Bouneffouf, D., Bouzeghoub, A., Gançarski, A.L.: Following the user’s interests in mobile context-aware recommender systems: The hybrid-e-greedy algorithm. Proceedings - 26th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012 (2012) 657–662
Hussein, T., Linder, T., Gaulke, W., Ziegler, J.: Hybreed: A software framework for developing context-aware hybrid recommender systems. User Modeling and User-Adapted Interaction 24 (2014) 121–174
Kim, J., Lee, D., Chung, K.Y.: Item recommendation based on context-aware model for personalized u-healthcare service. Multimedia Tools and Applications 71(2) (2014) 855–872
Lee, W.P., Lee, K.H.: Making smartphone service recommendations by predicting users’ intentions: A context-aware approach. Information Sciences 277 (2014) 21–35
Li, L., Zheng, L., Yang, F., Li, T.: Modeling and broadening temporal user interest in personalized news recommendation. Expert Systems with Applications 41(7) (2014) 3168–3177
Colombo-Mendoza, L.O., Valencia-Garca, R., Rodrguez-González, A., Alor-Hernández, G., Samper-Zapater, J.J.: RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes. Expert Systems with Applications 42(3) (February 2015) 1202–1222
Campos, P.G., Dez, F., Cantador, I.: Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols. User Modeling and User-Adapted Interaction 24(1-2) (February 2013) 67–119
Alhamid, M.F., Rawashdeh, M., Al Osman, H., Hossain, M.S., El Saddik, A.: Towards context-sensitive collaborative media recommender system. Multimedia Tools and Applications (2014)
Hawalah, A., Fasli, M.: Utilizing contextual ontological user profiles for personalized recommendations. Expert Systems with Applications 41(10) (2014) 4777–4797
Harvey, M., Ludwig, B., Elsweiler, D.: You are what you eat : learning user tastes for rating prediction. 1–12
Skillen, K.L., Chen, L., Nugent, C.D., Donnelly, M.P., Burns, W., Solheim, I.: Ontological user profile modeling for context-aware application personalization. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 7656 LNCS. (2012) 261–268
Verbert, K., Manouselis, N.: Context-aware recommender systems for learning: a survey and future challenges. Learning … 5(4) (2012) 318–335
Heckmann, D.: Ubiquitous User Modeling. Volume 297. (2005)
Heckmann, D., Schwartz, T., Brandherm, B.: GUMO the General User Model Ontology. User modeling … (2005)
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Inzunza, S., Juárez-Ramírez, R., Ramírez-Noriega, A. (2016). User and Context Information in Context-Aware Recommender Systems: A Systematic Literature Review. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Mendonça Teixeira, M. (eds) New Advances in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 444. Springer, Cham. https://doi.org/10.1007/978-3-319-31232-3_61
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DOI: https://doi.org/10.1007/978-3-319-31232-3_61
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