Skip to main content

Group Recommender Systems: State of the Art, Emerging Aspects and Techniques, and Research Challenges

  • Conference paper
Advances in Information Retrieval (ECIR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9626))

Included in the following conference series:

Abstract

A recommender system aims at suggesting to users items that might interest them and that they have not considered yet. A class of systems, known as group recommendation, provides suggestions in contexts in which more than one person is involved in the recommendation process. The goal of this tutorial is to provide the ECIR audience with an overview on group recommendation. We will first illustrate the recommender systems principles, then formally introduce the problem of producing recommendations to groups, and present a survey based on the tasks performed by these systems. We will also analyze challenging topics like their evaluation, and present emerging aspects and techniques in this area. The tutorial will end with a summary that highlights open issues and research challenges.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Amer-Yahia, S., Omidvar-Tehrani, B., Basu Roy, S., Shabib, N.: Group recommendation with temporal affinities. In: Proceedings of 18th International Conference on Extending Database Technology (EDBT), pp. 421–432. OpenProceedings.org (2015)

    Google Scholar 

  2. Boratto, L., Carta, S.: State-of-the-art in group recommendation and new approaches for automatic identification of groups. In: Soro, A., Vargiu, E., Armano, G., Paddeu, G. (eds.) IRMDE 2010. SCI, vol. 324, pp. 1–20. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  3. Boratto, L., Carta, S.: Using collaborative filtering to overcome the curse of dimensionality when clustering users in a group recommender system. In: ICEIS 2014 - Proceedings of 16th International Conference on Enterprise Information Systems, vol. 2. pp. 564–572. SciTePress (2014)

    Google Scholar 

  4. Carvalho, L.A.M., Macedo, H.T.: Generation of coalition structures to provide proper groups’ formation in group recommender systems. In: Proceedings of 22nd International Conference on World Wide Web Companion, pp. 945–950. International World Wide Web Conferences Steering Committee (2013)

    Google Scholar 

  5. Chen, J., Liu, Y., Li, D.: Dynamic group recommendation with modified collaborative filtering and temporal factor. Int. Arab J. Inf. Technol. (IAJIT) (2014)

    Google Scholar 

  6. Christensen, I.A., Schiaffino, S.: Social influence in group recommender systems. Online Inf. Rev. 38(4), 524–542 (2014)

    Article  Google Scholar 

  7. Jameson, A., Smyth, B.: Recommendation to groups. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 596–627. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  8. Kim, H.N., Saddik, A.E.: A stochastic approach to group recommendations in social media systems. Inf. Syst. 50, 76–93 (2015)

    Article  Google Scholar 

  9. Masthoff, J.: Group recommender systems: combining individual models. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 677–702. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  10. Ricci, F.: Recommender systems: models and techniques. In: Alhajj, P., Rokne, J. (eds.) Encyclopedia of Social Network Analysis and Mining, pp. 1511–1522. Springer, New York (2014)

    Google Scholar 

  11. Ricci, F., Rokach, L., Shapira, B.: Recommender systems: introduction and challenges. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 1–34. Springer, Heidelberg (2015). doi:10.1007/978-1-4899-7637-6_1

    Chapter  Google Scholar 

  12. Yuan, Q., Cong, G., Lin, C.Y.: COM: a generative model for group recommendation. In: Proceedings of 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014, pp. 163–172. ACM (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ludovico Boratto .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Boratto, L. (2016). Group Recommender Systems: State of the Art, Emerging Aspects and Techniques, and Research Challenges. In: Ferro, N., et al. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science(), vol 9626. Springer, Cham. https://doi.org/10.1007/978-3-319-30671-1_87

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30671-1_87

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30670-4

  • Online ISBN: 978-3-319-30671-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics