基于信任的协同过滤算法

Xiaowei Xu, Fudong Wang
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引用次数: 5

摘要

互联网的飞速发展将我们带入了信息爆炸的时代,个性化推荐系统的广泛应用也随之而来。协同过滤推荐算法是个性化推荐系统中应用最广泛的算法,但它面临着数据稀疏性、冷启动、“闲人”攻击等问题。随着社交网络的发展,许多电子商务网站、社交网站引入信任机制,这成为克服传统协同过滤算法存在问题的新途径。本文首先介绍了协同过滤推荐算法及存在的问题,然后总结了目前基于信任的协同过滤算法。对于基于信任的协同过滤算法,本文总结了信任表达式和度量,重点分析了具有代表性的信任模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trust -Based Collaborative Filtering Algorithm
The rapid development of internet has brought us into the era of information explosion, which brings the widespread application of the personalized recommendation system. Collaborative filtering recommendation algorithm is the most widely used algorithms in the personalized recommended system, but it faces problems like the data sparsity, cold start," idler" attack. with the development of social network, many e-commerce sites, social network sites introduce the trust mechanism, which becomes the new approach to overcome the problems of the traditional collaborative filtering algorithms. This paper first introduces the collaborative filtering recommendation algorithm and the existing problems, and then summarizes the current trust based collaborative filtering algorithms. for the trust based collaborative filtering algorithms, this paper summarizes the trust expressions and metrics, and focus on analyzing the representative trust models.
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