Improving group recommendations with consensus reaching processes

Francisco Moya, Jorge de Castro, Francisco J. Quesada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recommender systems help users when large amounts of information are available,filtering those pieces of information by taking into account users' preferences or needs. These systems have been successfully used in diverse areas, such as e-commerce or tourism. To extend these systems Group Recommender Systems were proposed to address the problem of recommending items to group of users with different interests. In order to compute group recommendations, aggregation processes over individual recommendation lists have been applied.But this aggregation does not take into account group dynamics such as influence of group on individual preferences or consensus processes. To overcome these limitations, we try to bring consensus into group recommendations inspired by Consensus Reaching Processes in Group Decision Making. Computing recommendations in this way makes them reaching a high level of consensus amongst group members which improves previous results.
Original languageEnglish
Title of host publicationEureka International Virtual Physical Meeting Eureka 2014
Number of pages1
Publication statusPublished - 2014

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