2014/11/15 by Hao Liao, Liao, Hao, An Zeng +3
Computer Science · Decision Sciences · Physics and Astronomy · #Expert finding and Q&A systems #FOS: Computer and information sciences #Game Theory and Applications #Information Retrieval (cs.IR) #Opinion Dynamics and Social Influence
paper · pdf · doi:10.48550/arxiv.1411.4972
openalex publication_date 2014/11/15 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Online reputation systems are commonly used by e-commerce providers nowadays. In order to generate an objective ranking of online items' quality according to users' ratings, many sophisticated algorithms have been proposed in the literature. In this paper, instead of proposing new algorithms we focus on a more fundamental problem: the rating projection. The basic idea is that even though the rating values given by users are linearly separated, the real preference of users to items between different values gave is nonlinear. We thus design an approach to project the original ratings of users to more representative values. This approach can be regarded as a data pretreatment method. Simulation in both artificial and real networks shows that the performance of the ranking algorithms can be improved when the projected ratings are used.