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Negotiation framework for group recommendation based on fuzzy computational model of trust and distrust

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Abstract

Group recommender system (GRS) is the gradually prospering type of recommender system (RS) which tends to provide recommendations for the group of users rather than the individual. Most of the existing GRS obtain group preferences using equal weighing of the individual preferences, ignoring the relationship among group members within the group. But this is not a practical scenario because each member has different behavior. Therefore, in this article, we introduce a multiagent based negotiation mechanism between agents, each of them acts in favor of one group member. The proposed negotiation protocol allows agents to accept or discard a part of the offer based on trust and distrust among users, which gives more agility to the negotiation process. Further, we use memory for each agent in the group that records the previously proposed offers for that agent. The efficiency of trust-distrust enhanced GRSs is compared with traditional techniques and the outcomes of computational experiments confirm the supremacy of our proposed models over baseline GRSs techniques.

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Notes

  1. https://grouplens.org/datasets/movielens/100k/

  2. https://snap.stanford.edu/data/soc-sign-epinions.html

  3. https://www2.informatik.uni-freiburg.de/~cziegler/BX/

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Correspondence to Nirmal Choudhary.

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Choudhary, N., Minz, S. & Bharadwaj, K.K. Negotiation framework for group recommendation based on fuzzy computational model of trust and distrust. Multimed Tools Appl 79, 27337–27364 (2020). https://doi.org/10.1007/s11042-020-09339-x

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  • DOI: https://doi.org/10.1007/s11042-020-09339-x

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