Skip to main content
Log in

Group context-aware recommendation systems

  • Published:
Scientific and Technical Information Processing Aims and scope

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. 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.

    Chapter  Google Scholar 

  2. 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.

    Article  Google Scholar 

  3. 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.

    Google Scholar 

  4. Shilov, N., Group recommending systems for configuration of flexible net organizations, in Informatsionnoupravlyayushchie sistemy (Information-Managing Systems), No. 5, St. Petersburg: Politekhnika, 2012.

    Google Scholar 

  5. 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.

    Google Scholar 

  6. 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.

    Article  Google Scholar 

  7. 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.

    Google Scholar 

  8. 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.

    Google Scholar 

  9. 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.

    Google Scholar 

  10. 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.

    Google Scholar 

  11. Romesburg, H.C., Cluster Analysis for Researchers, California: Lulu, 2004, p. 340.

    Google Scholar 

  12. 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.

    Article  Google Scholar 

  13. Baeza-Yates, R. and Ribeiro-Neto, B., Modern Information Retrieval. Addison-Wesley, 1999, p. 513.

    Google Scholar 

  14. Salton, G., Automatic Text Processing: The Transformation Analysis and Retrieval of Information by Computer, Addison-Wesley, 1989.

    Google Scholar 

  15. Belkin, N. and Croft, B., Information filtering and information retrieval, Commun. ACM, 1992, vol. 35, no. 12 (Sp. Num.), pp. 29–37.

    Article  Google Scholar 

  16. Adomavicius, G., Mobasher, B., Ricci, F., and Tuzhilin, A., Context-aware recommender systems, AI Magazine, 2011, vol. 32, no. 3, pp. 67–80.

    Google Scholar 

  17. 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.

    Article  Google Scholar 

  18. 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.

    Chapter  Google Scholar 

  19. 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.

    Google Scholar 

  20. Baltrunas, L. and Ricci, F., Context-dependent recommendations with items splitting, Proc. 1st Italian Information Retrieval Workshop, 2010, Padua, Italy, pp. 71–75.

    Google Scholar 

  21. Koren, Y., Bell, R., and Volinsky, C., Matrix factorization techniques for recommender systems, IEEE Computer, 2009, vol. 42, no. 8, pp. 30–37.

    Article  Google Scholar 

  22. Rendle, S., Factorization machines with libFM, ACM Trans. Intell. Syst. Technol., 2012, vol. 3, no. 3, p. 57 (1–22).

    Article  Google Scholar 

  23. 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).

    Article  Google Scholar 

  24. 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.

    Google Scholar 

  25. 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.

    Google Scholar 

  26. 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.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. V. Smirnov.

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

Check for updates. Verify currency and authenticity via CrossMark

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0147688214050050

Keywords

Navigation