IEDC: An integrated approach for overlapping and non-overlapping community detection
نویسندگان
چکیده
منابع مشابه
IEDC: An Integrated Approach for Overlapping and Non-overlapping Community Detection
Community detection is a task of fundamental importance in social network analysis. Community structures enable us to discover the hidden interactions among the network members that can be used in many knowledge-based domains such as bioinformatics, computer networks, e-commerce and forensic science. While there exist many works on community detection based on connectivity structure, they suffe...
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Overlapping community detection has recently drawn much attention in the field of social network analysis. In this paper, we propose a notion of hesitant node (HN) in network with overlapping community structure. An HN is a special kind of node that contacts with multiple communities but the communication is not frequent or even accidental, thus its community structure is implicit and its class...
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Community detection is a task of fundamental importance in social network analysis. Community structures enable us to discover the hidden interactions among the network entities and summarize the network information that can be applied in many applied domains such as bioinformatics, finance, e-commerce and forensic science. There exist a variety of methods for community detection based on diffe...
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Recently, community detection in complex networks has attracted more and more attentions. However, real networks usually have number of overlapping communities. Many overlapping community detection algorithms have been developed. These methods usually consider the overlapping community detection as a single-objective optimization problem. This paper regards it as a multi-objective optimization ...
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ژورنال
عنوان ژورنال: Knowledge-Based Systems
سال: 2017
ISSN: 0950-7051
DOI: 10.1016/j.knosys.2017.02.018