A GROUP RECOMMENDATION SYSTEM FOR MOVIES BASED ON MAS

A GROUP RECOMMENDATION SYSTEM FOR MOVIES BASED ON MAS

Authors:
Christian Paulo VILLAVICENCIO, Silvia SCHIAFFINO, J. Andrés DÍAZ-PACE, Ariel MONTESERIN

DOI:
10.14201/ADCAIJ201653112

Volume:
Regular Issue 5 (3), 2016

Keywords: 
Multi-Agent Systems; Recommender Systems; Group Recommendation

Providing recommendations to groups of users has become popular in many applications today. Although several group recommendation techniques exist, the generation of items that satisfy all group members in an even way still remains a challenge. To this end, we have developed a multi-agent approach called PUMAS-GR that relies on negotiation techniques to improve group recommendations. We applied PUMAS-GR to the movies domain, and used the monotonic concession protocol to reach a consensus on the movies proposed to a group.

JCR

Position in 2022 Journal Citation Indicator (JCI) Ranking:
Category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE


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