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An Altruistic-Based Utility Function for Group Recommendation

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Transactions on Computational Collective Intelligence XXVIII

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 10780))

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Abstract

Preference aggregation strategies, that are inspired by economic models of decision makers, typically assume that the individual preferences of the group members depend only on their own individual evaluations of the considered items. In this direction, group recommendation algorithms rely on such standard aggregation techniques that do not consider the possibility of evaluating social interactions and influences among group’s members, as well as their personalities, which are, indeed, crucial factors in the group’s decision-making process, especially regarding small groups. On the contrary, the laboratory data have encouraged the development of models of other-regarding preferences since altruism, fairness, and reciprocity strongly motivate many people. In this paper, starting from a utility function from the literature, which combines the user personal evaluation of an item with the ones of the other group members, we propose a group recommendation method that takes into account altruism. Such function models the level of a user’s altruistic behavior starting from his/her agreeableness personality trait. Once such utility values are evaluated, the goal is to recommend items that maximize the social welfare. Performance is evaluated with a pilot study and compared with respect to Least Misery. Results showed that while for groups of two people Least Misery performs slightly better, in the other cases the two methods are comparable.

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Notes

  1. 1.

    Status describes the role that a person has in a social group.

  2. 2.

    http://mahout.apache.org/.

  3. 3.

    The ACM Conference on Recommendation Systems (RecSys) is the most important international conference in the field of recommendation systems. For more info visit: https://recsys.acm.org/, https://recsys.acm.org/recsys14/challenge-workshop/.

  4. 4.

    https://www.android.com.

  5. 5.

    https://www.java.com/.

  6. 6.

    https://spring.io.

  7. 7.

    http://tomcat.apache.org.

  8. 8.

    http://www.omdbapi.com - The Open Movie Database is a free web service to obtain movie information.

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Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, University of Naples Federico II, Via Claudio, 80125, Napoli, Italy

    Silvia Rossi & Francesco Cervone

  2. Dipartimento di Matematica e Applicazioni, University of Naples Federico II, Via Cintia, 80126, Napoli, Italy

    Francesco Barile

Authors
  1. Silvia Rossi
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  2. Francesco Cervone
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  3. Francesco Barile
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Corresponding author

Correspondence to Silvia Rossi .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Swinburne University of Technology, Hawthorn, Victoria, Australia

    Ryszard Kowalczyk

  3. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  4. Universidade do Porto, Porto, Portugal

    Ana Paula Rocha

  5. INSTICC, Polytechnic Institute of Setúbal, Setubal, Portugal

    Joaquim Filipe

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Rossi, S., Cervone, F., Barile, F. (2018). An Altruistic-Based Utility Function for Group Recommendation. In: Nguyen, N., Kowalczyk, R., van den Herik, J., Rocha, A., Filipe, J. (eds) Transactions on Computational Collective Intelligence XXVIII. Lecture Notes in Computer Science(), vol 10780. Springer, Cham. https://doi.org/10.1007/978-3-319-78301-7_2

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