计算机科学 ›› 2014, Vol. 41 ›› Issue (8): 90-93.doi: 10.11896/j.issn.1002-137X.2014.08.019
• 2013年全国理论计算机科学学术年会 • 上一篇 下一篇
张绍武,林鸿飞,刘晓霞,窦彦昭
ZHANG Shao-wu,LIN Hong-fei,LIU Xiao-xia and DOU Yan-zhao
摘要: 社会网络中,用户之间的信任关系可以为用户判别信息是否可信提供依据。现有的信任计算方法一般是通过搜索节点之间的路径,再在其上添加各种其它限制,如路径长度、信任度下界等来计算信任度,而考虑节点之间的相似性的方法却很少。从节点之间的相似性出发,在信任传播模型的基础上,结合贝叶斯条件概率公式,提出了基于概率的信任传播模型。同时分析了信任传播模型中衰减系数对结果的影响;通过统计分析数据,得出具有信任关系的用户之间的相似度要比不具有信任关系的用户之间的相似度高得多,从而证明了贝叶斯理论可显著提高信任传播算法 的有效性。在Epinion数据集上进行的实验证明了该方法的有效性。
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