Discovering and Profiling Overlapping Communities in Location-Based Social Networks
نویسندگان
چکیده
منابع مشابه
Detecting Overlapping Communities in Social Networks using Deep Learning
In network analysis, a community is typically considered of as a group of nodes with a great density of edges among themselves and a low density of edges relative to other network parts. Detecting a community structure is important in any network analysis task, especially for revealing patterns between specified nodes. There is a variety of approaches presented in the literature for overlapping...
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Complex networks can be typically broken down into groups or modules. Discovering this “community structure” is an important step in studying the large-scale structure of networks. Many algorithms have been proposed for community detection and benchmarks have been created to evaluate their performance. Typically algorithms for community detection either partition the graph (nonoverlapping commu...
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Identifying communities is essential for understanding the dynamics of a social network. The prevailing approach to the problem of community discovery is to partition the network into disjoint groups of members that exhibit a high degree of internal communication. This approach ignores the possibility that an individual may belong to two or more groups. Increasingly, researchers have begun to e...
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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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The categorization of vertices in a network is a common task across a multitude of domains. Specifically, structural divisions into internally well connected sets have been shown to be useful in computer science, social science, and biology. In each of these areas, grouping vertices using structural boundaries helps one to understand the underlying processes of a network. Identifying such group...
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ژورنال
عنوان ژورنال: IEEE Transactions on Systems, Man, and Cybernetics: Systems
سال: 2014
ISSN: 2168-2216,2168-2232
DOI: 10.1109/tsmc.2013.2256890