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Toward Socially Agreeable Aggregate Functions for Group Recommender Systems  

Ok, Chang-Soo (Department of Industrial Engineering, Pennsylvania State University)
Lee, Seok-Cheon (School of Industrial Engineering, Purdue University)
Jeong, Byung-Ho (Department of Industrial Engineering, The Research Center of Industrial technology, Chonbuk University)
Publication Information
Journal of the Korean Operations Research and Management Science Society / v.32, no.4, 2007 , pp. 61-75 More about this Journal
Abstract
In ubiquitous computing, shared environments are required to adapt to people intelligently. Based on information about user preferences, the shared environments should be adjusted so that all users in a group are satisfied as possible. Although many group recommender systems have been proposed to obtain this purpose, they only consider average and misery. However, a broad range of philosophical approaches suggest that high inequality reduces social agreeability, and consequently causes users' dissatisfactions. In this paper, we propose social welfare functions, which consider inequalities in users' preferences, as alternative aggregation functions to achieve a social agreeability. Using an example in a previous work[7], we demonstrate the effectiveness of proposed welfare functions as socially agreeable aggregate functions in group recommender systems.
Keywords
Group Recommender; Recommender Systems; Ubiquitous; Social Welfare Function;
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