A heuristic local community detection method (HLCD)

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• 作者：Mohammad Ali Tabarzad ; Ali Hamzeh
• 关键词：Local community detection ; Social networks
• 刊名：Applied Intelligence
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：46
• 期：1
• 页码：62-78
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence (incl. Robotics); Mechanical Engineering; Manufacturing, Machines, Tools;
• 出版者：Springer US
• ISSN：1573-7497
• 卷排序：46

文摘

The advances in social networks has led to the concentration of research on analyzing people’s behaviors in these networks. Accordingly, detecting communities and the interactions between their members is one of the most important issues addressed by these studies. After the proposition of new community detection methods in recent years, due to the extensive volume of the information generated in social networks and the increasing growth in the size of these networks, researchers became more interested in local, rather than global, detection methods. This paper proposes a heuristic approach to detecting communities by investigating local information. Comparing this method with state-of-the-art approaches, it is observed that the proposed approach outperforms the compared methods in detecting communities and their members and provides more accurate results.