A survey of clustering large probabilistic graphs: Techniques, evaluations, and applications

Malihe Danesh; Morteza Dorrigiv; Farzin Yaghmaee

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A survey of clustering large probabilistic graphs: Techniques, evaluations, and applications

机译：A survey of clustering large probabilistic graphs: Techniques, evaluations, and applications

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Given the growth of uncertainty in the real world, analysing probabilistic graphs iscrucial. Clustering is one of the most fundamental methods of mining probabilisticgraphs to discover the hidden patterns in them. This survey examines an extensiveand organized analysis of the clustering techniques of large probabilistic graphs proposedin the literature. First, the definition of probabilistic graphs and modelling themare introduced. Second, the clustering of such graphs and their challenges, such asuncertainty of edges, high dimensions, and the impossibility of applying certain graphclustering techniques directly, are expressed. Then, a taxonomy of clusteringapproaches is discussed in two main categories: threshold-based and possibleworlds-based methods. The techniques presented in each category are explained andexamined. Here, these methods are evaluated on real datasets, and their performanceis compared with each other. Finally, the survey is summarized by describing some ofthe applications of probabilistic graph clustering and future research directions.

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来源
《Expert systems: The international journal of knowledge engineering》 |2023年第6期|e3248.1-e3248.20|共20页
作者
Malihe Danesh; Morteza Dorrigiv; Farzin Yaghmaee;
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作者单位

Department of Computer Engineering,University of Science and Technology ofMazandaran, Behshahr, Iran;

Faculty of Electrical and ComputerEngineering, Semnan University, Semnan, Iran;

Faculty of Electrical and ComputerEngineering, Semnan University, Semnan, Iran;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类
关键词
clustering; possible worlds-based methods; probabilistic graph; threshold-based methods;

A survey of clustering large probabilistic graphs: Techniques, evaluations, and applications

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