research-article

Social factors in group recommender systems

Authors:

Lara Quijano-Sanchez,

Juan A. Recio-Garcia,

Belen Diaz-Agudo,

Guillermo Jimenez-DiazAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 4, Issue 1

Article No.: 8, Pages 1 - 30

https://doi.org/10.1145/2414425.2414433

Published: 01 February 2013 Publication History

Abstract

In this article we review the existing techniques in group recommender systems and we propose some improvement based on the study of the different individual behaviors when carrying out a decision-making process. Our method includes an analysis of group personality composition and trust between each group member to improve the accuracy of group recommenders. This way we simulate the argumentation process followed by groups of people when agreeing on a common activity in a more realistic way. Moreover, we reflect how they expect the system to behave in a long term recommendation process. This is achieved by including a memory of past recommendations that increases the satisfaction of users whose preferences have not been taken into account in previous recommendations.

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Cited By

Delić AEmamgholizadeh HRicci FMasthoff J(2024)Supporting Group Decision-Making: Insights from a Focus Group StudyProceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3627043.3659538(301-306)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3627043.3659538
Kwak DPark SCha IKim HLim Y(2024)Investigating the Potential of Group Recommendation Systems As a Medium of Social Interactions: A Case of Spotify Blend Experiences between Two UsersProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642544(1-15)Online publication date: 11-May-2024
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Liang Y(2024)FAER: Fairness-Aware Event-Participant Recommendation in Event-Based Social NetworksIEEE Transactions on Big Data10.1109/TBDATA.2024.337240910:5(655-668)Online publication date: Oct-2024
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Index Terms

Social factors in group recommender systems
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Published In

cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 4, Issue 1

Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context

January 2013

357 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/2414425

Issue’s Table of Contents

Copyright © 2013 ACM.

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Association for Computing Machinery

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Publication History

Published: 01 February 2013

Accepted: 01 July 2011

Revised: 01 April 2011

Received: 01 January 2011

Published in TIST Volume 4, Issue 1

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Cited By

Delić AEmamgholizadeh HRicci FMasthoff J(2024)Supporting Group Decision-Making: Insights from a Focus Group StudyProceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3627043.3659538(301-306)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3627043.3659538
Kwak DPark SCha IKim HLim Y(2024)Investigating the Potential of Group Recommendation Systems As a Medium of Social Interactions: A Case of Spotify Blend Experiences between Two UsersProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642544(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642544
Liang Y(2024)FAER: Fairness-Aware Event-Participant Recommendation in Event-Based Social NetworksIEEE Transactions on Big Data10.1109/TBDATA.2024.337240910:5(655-668)Online publication date: Oct-2024
https://doi.org/10.1109/TBDATA.2024.3372409
Bukhari MMaqsood MAadil F(2024)KGR: A Kernel-Mapping Based Group Recommender System Using Trust RelationsNeural Processing Letters10.1007/s11063-024-11639-456:4Online publication date: 19-Jun-2024
https://doi.org/10.1007/s11063-024-11639-4
Son NGiap CSon LGiang NTuan TGerogiannis VTzimos D(2024)A dynamic fuzzy group recommender system based on intuitionistic fuzzy choquet integral aggregationSoft Computing10.1007/s00500-023-09485-yOnline publication date: 3-Jan-2024
https://doi.org/10.1007/s00500-023-09485-y
Huang CLin Y(2024)Influence Based Group Recommendation System in Personality and Dynamic TrustHCI International 2024 Posters10.1007/978-3-031-61966-3_6(50-57)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-61966-3_6
Howell PAryal AWu C(2023)Web-Based Patient Recommender Systems for Preventive Care: Protocol for Empirical Research PropositionsJMIR Research Protocols10.2196/4331612(e43316)Online publication date: 30-Mar-2023
https://doi.org/10.2196/43316
Delic AEmamgholizadeh HRicci F(2023)CHARM: A Group Recommender ChatBotAdjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization10.1145/3563359.3597388(275-282)Online publication date: 26-Jun-2023
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Barile FDelic APeška LSaccardi IUlusoy OVinella F(2023)GMAP 2023: 2nd Workshop on Group Modeling, Adaptation and PersonalizationAdjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization10.1145/3563359.3595628(249-252)Online publication date: 26-Jun-2023
https://dl.acm.org/doi/10.1145/3563359.3595628
Ye JXiong HGuo JMeng X(2023)A group recommender system for books based on fine-grained classification of commentsThe Electronic Library10.1108/EL-11-2022-025241:2/3(326-346)Online publication date: 1-May-2023
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