Trustable aggregation of online ratings

Hyun-Kyo Oh, Sang-Wook Kim, Sunju Park, M. Zhou
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引用次数: 5

Abstract

The average of the customer ratings on the product, which we call reputation, is one of the key factors in online purchasing decision of a product. There is, however, no guarantee in the trustworthiness of the reputation since it can be manipulated rather easily. In this paper, we define false reputation as the problem of the reputation to be manipulated by unfair ratings, and design a general framework that provides trustable reputation. For this purpose, we propose TRUEREPUTATION, an algorithm that iteratively adjusts the reputation based on the confidence of customer ratings.
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可靠的在线评级汇总
顾客对产品的平均评价,即我们所说的信誉,是在线购买产品决策的关键因素之一。然而,由于声誉很容易被操纵,因此无法保证声誉的可信度。在本文中,我们将虚假声誉定义为声誉被不公平评级操纵的问题,并设计了一个提供可信声誉的一般框架。为此,我们提出了trureputation,这是一种基于客户评级置信度迭代调整声誉的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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