Abstract
The architecture and basic models of a context-aware recommendation system based on collaborative filtering are proposed. The major problems in creating such systems are emphasized and methods for solving the problems are proposed. The advantages of the pre-filtering methods that are used to allow for context are substantiated. Basic processes of constructing recommendations are described. The proposed architecture is demonstrated using a recommendation system for an m-tourism application.
Similar content being viewed by others
References
Garcia, I., Sebastia, L., Onaindia, E., and Guzman, C.A., Group recommender system for tourist activities, Proc. 10th Int. Conf. “E-Commerce and Web Technologies” 2009, pp. 26–37.
Moon, S.K., Simpson, T.W., and Kumara, S.R.T., An agent-based recommender system for developing customized families of products, J. Intell. Manufact., 2009, vol. 20, pp. 649–659.
Chen, Y.-J., Chen, Y.-M., and Wu, M.-S., An expert recommendation system for product empirical knowledge consultation, ICCSIT2010: The 3rd IEEE Int. Conf. on Computer Science and Information Technology, 2010, pp. 23–27.
Shilov, N., Group recommending systems for configuration of flexible net organizations, in Informatsionnoupravlyayushchie sistemy (Information-Managing Systems), No. 5, St. Petersburg: Politekhnika, 2012.
McCarthy, K., Salamo, M., Coyole, L., McGinty, L., Smyth, B., and Nixon, P., Group recommender systems: A critiquing based approach, Proc. 11th Int. Conf. on Intelligent User Interfaces, 2006, pp. 267–269.
Adomavicius, G. and Tuzhilin, A., Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions, IEEE Trans. Knowl. Data Eng., 2005, vol. 17, pp. 734–749.
Shilov, N., Problems of solution taking support at configuration of flexible net organizations, Trudy St. Petersburg. Issled. Inst. Ross. Akad. Nauk, 2012, no. 22, pp. 224–233.
Smirnov, A. and Shilov, N., Collaborative recommendation systems for PLM: Approach and technological frame-work, Proc. 8th Int. Product Lifecycle Management Conf. PLM11 2011, pp. 11–13.
Smirnov, A.V. and Shilov, N.G., Group recommendation systems for management of life cycle of articles: Approach and technologies, Izv. YuFU. Tekhn. Nauki, 2011, no. 5, pp. 203–206.
Baatarjav, E.-A., Phithakkitnukoon, S., and Dantu, R., Group recommendation system for facebook, Proc. on the Move to Meaningful Internet Systems Workshop, 2008, pp. 211–219.
Romesburg, H.C., Cluster Analysis for Researchers, California: Lulu, 2004, p. 340.
Flake, G.W., Lawrence, S., Giles, C.L., and Coetzee, F., Self-organization and identification of Web communities, IEEE Computer, 2002, vol. 35, no. 3, pp. 66–71.
Baeza-Yates, R. and Ribeiro-Neto, B., Modern Information Retrieval. Addison-Wesley, 1999, p. 513.
Salton, G., Automatic Text Processing: The Transformation Analysis and Retrieval of Information by Computer, Addison-Wesley, 1989.
Belkin, N. and Croft, B., Information filtering and information retrieval, Commun. ACM, 1992, vol. 35, no. 12 (Sp. Num.), pp. 29–37.
Adomavicius, G., Mobasher, B., Ricci, F., and Tuzhilin, A., Context-aware recommender systems, AI Magazine, 2011, vol. 32, no. 3, pp. 67–80.
Adomavicius, G., Sankaranarayanan, R., Sen, S., and Tuzhilin, A., Incorporating contextual information in recommender systems using a multidimensional approach, ACM Trans. Inf. Syst., 2005, vol. 23, no. 1, pp. 103–145.
Codina, V., Ricci, F., and Ceccaroni, L., Semantically-enhanced pre-filtering for context-aware recommender systems, Proc. 3rd Workshop on Context-Awareness in Retrieval and Recommendation, New York: 2013, pp. 15–18.
Baltrunas, L. and Ricci, F., Context-based splitting of item ratings in collaborative filtering, Proc. 3rd ACM Conf. on Recommender Systems, 2009, pp. 245–248.
Baltrunas, L. and Ricci, F., Context-dependent recommendations with items splitting, Proc. 1st Italian Information Retrieval Workshop, 2010, Padua, Italy, pp. 71–75.
Koren, Y., Bell, R., and Volinsky, C., Matrix factorization techniques for recommender systems, IEEE Computer, 2009, vol. 42, no. 8, pp. 30–37.
Rendle, S., Factorization machines with libFM, ACM Trans. Intell. Syst. Technol., 2012, vol. 3, no. 3, p. 57 (1–22).
Shi, Y., Larson, M., and Hanjalic, A., Mining contextual movie similarity with matrix factorization for context-aware recommendation, ACM Trans. Intell. Syst. Technol., 2013, vol. 4, no. 1, p. 16 (1–19).
Smirnov, A.V., Pashkin, M.P., Shilov, N.G., and Levashova, T.V., Approach to construction of distributed system of intellectual support of solution taking in open information medium, Trudy St. Petersburg. Issled. Inst. Ross. Akad. Nauk, 2007, vol. 1, no. 4, pp. 36–49.
Kashevnik, A.M. and Teslya, N.N., Automated system of joint utilization of autotransport, Materialy konferentsii “Informatsionnye tekhnologii v upravlenii” (ITU-2012) (Proc. Conf. Information Technologies in Management (ITU-2012)), St. Petersburg: Elektropribor, 2012.
Boratto, L., Carta, S., Chessa, A., and Agelli, M., Group recommendation with automatic identification of user communities, Proc. IEEE/WIC/ACM Int. Joint Conf. on Web Intelligence and Intelligent Agent Technologies, 2009, vol. 3, pp. 547–550.
Author information
Authors and Affiliations
Corresponding author
Additional information
Original Russian Text © A.V. Smirnov, N.G. Shilov, A.V. Ponomarev, A.M. Kashevnik, V.G. Parfenov, 2013, published in Iskusstvennyi Intellekt i Prinyatie Reshenii, 2013, No. 3, pp. 14–25.
About this article
Cite this article
Smirnov, A.V., Shilov, N.G., Ponomarev, A.V. et al. Group context-aware recommendation systems. Sci. Tech.Inf. Proc. 41, 325–334 (2014). https://doi.org/10.3103/S0147688214050050
Published:
Issue Date:
DOI: https://doi.org/10.3103/S0147688214050050