结合链接类型值的社会网络分类

R. Heatherly, Murat Kantarcioglu, B. Thuraisingham
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引用次数: 25

摘要

社会网络中节点的分类及其在安全信息学中的应用已经得到了广泛的研究。然而,以前的工作通常没有考虑连接社交网络成员的链接类型(例如,一个人是朋友还是亲密朋友)以进行分类。在这里,我们提出了改进的朴素贝叶斯分类方案,以利用分类任务中的链接类型信息。基本上,我们提出了两种新的贝叶斯分类方法来扩展传统的关系朴素贝叶斯分类器,即链接型关系贝叶斯分类器和加权链接型贝叶斯分类器。然后,我们通过对从互联网电影数据库获得的数据进行实验来证明我们提出的技术的有效性。
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Social network classification incorporating link type values
Classification of nodes in a social network and its applications to security informatics have been extensively studied in the past. However, previous work generally does not consider the types of links (e.g., whether a person is friend or a close friend) that connect social networks members for classification purposes. Here, we propose modified Naive Bayes Classification schemes to make use of the link type information in classification tasks. Basically, we suggest two new Bayesian classification methods that extend a traditional relational Naive Bayes Classifier, namely, the Link Type relational Bayes Classifier and the Weighted Link Type Bayes Classifier. We then show the efficacy of our proposed techniques by conducting experiments on data obtained from the Internet Movie Database.
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