Evaluating local community methods in networks
نویسندگان
چکیده
منابع مشابه
Evaluating Local Community Methods in Networks
The study of complex networks [1, 2, 3] has recently arisen as a powerful tool for understanding a variety of systems, such as biological and social interactions [4, 5], technology communications and interdependencies [1, 6], and many others. The problem of detecting communities, subsets of network nodes that are densely connected amongst themselves while being sparsely connected to other nodes...
متن کاملFinding and evaluating community structure in networks.
We propose and study a set of algorithms for discovering community structure in networks-natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using any one of a number of possible "betweenness" measures...
متن کاملLocal community extraction in directed networks
Network is a simple but powerful representation of real-world complex systems. Network community analysis has become an invaluable tool to explore and reveal the internal organization of nodes. However, only a few methods were directly designed for community-detection in directed networks. In this article, we introduce the concept of local community structure in directed networks and provide a ...
متن کاملFinding local community structure in networks.
Although the inference of global community structure in networks has recently become a topic of great interest in the physics community, all such algorithms require that the graph be completely known. Here, we define both a measure of local community structure and an algorithm that infers the hierarchy of communities that enclose a given vertex by exploring the graph one vertex at a time. This ...
متن کاملLocal Community Detection in Complex Networks
Community structure is an important aspect of network analysis, with a variety of reallife applications. Local community detection algorithms, which are relatively new in literature, provide the opportunity to analyze community structure in large networks without needing global information. We focus our work on a state-of-the-art algorithm developed by Yang and Leskovec and evaluate it on three...
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ژورنال
عنوان ژورنال: Journal of Statistical Mechanics: Theory and Experiment
سال: 2008
ISSN: 1742-5468
DOI: 10.1088/1742-5468/2008/05/p05001