Integrating Social Relationships and Personality into MAS-Based Group Recommendations
Recommender systems aim to predict the preferences of users and suggest items of interest to them in various domains. While traditional recommendation techniques consider users as individuals, some approaches aim to satisfy the needs of a group of people. Multi-agent systems can be used to develop s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/9/1/1 |
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| author | Ariel Monteserin Daiana Elin Madsen Daniela Godoy Silvia Schiaffino |
| author_facet | Ariel Monteserin Daiana Elin Madsen Daniela Godoy Silvia Schiaffino |
| author_sort | Ariel Monteserin |
| collection | DOAJ |
| description | Recommender systems aim to predict the preferences of users and suggest items of interest to them in various domains. While traditional recommendation techniques consider users as individuals, some approaches aim to satisfy the needs of a group of people. Multi-agent systems can be used to develop such recommendations, where multiple intelligent agents interact with each other to achieve a common goal, i.e., deciding which item to recommend. Particularly, negotiation techniques can be used to find a decision that aims at maximizing the satisfaction of all group members. The proposed approach introduces a multi-agent recommender system for a group of users by considering their personality traits, relationships and social interactions during the negotiation process that leads to the generation of recommendations. While traditional recommendation techniques do not take into account the effects of personality traits and relationships between individuals, our approach demonstrates that personality traits, especially personality types in the context of conflict management, and social relationships can significantly impact on the group recommendation. The results indicate that the opinion of an individual can be influenced when she is part of a group that cooperates towards a shared goal. Overall, the proposed approach shows that recommender systems can benefit from considering that factors. This work contributes to understanding the impact of personality traits and social relationships on group recommendations and suggests potential directions for future research. |
| format | Article |
| id | doaj-art-4e949893400e4d58b3a9c4806a8bfc03 |
| institution | Kabale University |
| issn | 2504-2289 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj-art-4e949893400e4d58b3a9c4806a8bfc032025-01-24T13:22:30ZengMDPI AGBig Data and Cognitive Computing2504-22892024-12-0191110.3390/bdcc9010001Integrating Social Relationships and Personality into MAS-Based Group RecommendationsAriel Monteserin0Daiana Elin Madsen1Daniela Godoy2Silvia Schiaffino3ISISTAN (Instituto de Sistemas Tandil), Facultad de Ciencias Exactas, Universidad Nacional del Centro de la Provincia de Buenos Aires, Tandil 7000, Buenos Aires, ArgentinaFacultad de Ciencias Exactas, Universidad Nacional del Centro de la Provincia de Buenos Aires Tandil, Tandil 7000, Buenos Aires, ArgentinaISISTAN (Instituto de Sistemas Tandil), Facultad de Ciencias Exactas, Universidad Nacional del Centro de la Provincia de Buenos Aires, Tandil 7000, Buenos Aires, ArgentinaISISTAN (Instituto de Sistemas Tandil), Facultad de Ciencias Exactas, Universidad Nacional del Centro de la Provincia de Buenos Aires, Tandil 7000, Buenos Aires, ArgentinaRecommender systems aim to predict the preferences of users and suggest items of interest to them in various domains. While traditional recommendation techniques consider users as individuals, some approaches aim to satisfy the needs of a group of people. Multi-agent systems can be used to develop such recommendations, where multiple intelligent agents interact with each other to achieve a common goal, i.e., deciding which item to recommend. Particularly, negotiation techniques can be used to find a decision that aims at maximizing the satisfaction of all group members. The proposed approach introduces a multi-agent recommender system for a group of users by considering their personality traits, relationships and social interactions during the negotiation process that leads to the generation of recommendations. While traditional recommendation techniques do not take into account the effects of personality traits and relationships between individuals, our approach demonstrates that personality traits, especially personality types in the context of conflict management, and social relationships can significantly impact on the group recommendation. The results indicate that the opinion of an individual can be influenced when she is part of a group that cooperates towards a shared goal. Overall, the proposed approach shows that recommender systems can benefit from considering that factors. This work contributes to understanding the impact of personality traits and social relationships on group recommendations and suggests potential directions for future research.https://www.mdpi.com/2504-2289/9/1/1group recommender systemsmulti-agent systemsnegotiationpersonality traitssocial relationships |
| spellingShingle | Ariel Monteserin Daiana Elin Madsen Daniela Godoy Silvia Schiaffino Integrating Social Relationships and Personality into MAS-Based Group Recommendations Big Data and Cognitive Computing group recommender systems multi-agent systems negotiation personality traits social relationships |
| title | Integrating Social Relationships and Personality into MAS-Based Group Recommendations |
| title_full | Integrating Social Relationships and Personality into MAS-Based Group Recommendations |
| title_fullStr | Integrating Social Relationships and Personality into MAS-Based Group Recommendations |
| title_full_unstemmed | Integrating Social Relationships and Personality into MAS-Based Group Recommendations |
| title_short | Integrating Social Relationships and Personality into MAS-Based Group Recommendations |
| title_sort | integrating social relationships and personality into mas based group recommendations |
| topic | group recommender systems multi-agent systems negotiation personality traits social relationships |
| url | https://www.mdpi.com/2504-2289/9/1/1 |
| work_keys_str_mv | AT arielmonteserin integratingsocialrelationshipsandpersonalityintomasbasedgrouprecommendations AT daianaelinmadsen integratingsocialrelationshipsandpersonalityintomasbasedgrouprecommendations AT danielagodoy integratingsocialrelationshipsandpersonalityintomasbasedgrouprecommendations AT silviaschiaffino integratingsocialrelationshipsandpersonalityintomasbasedgrouprecommendations |