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the small community phenomenon in networks: models, algorithms and applications
Peng Pan
2012
Conference Name9th Annual Conference on Theory and Applications of Models of Computation, TAMC 2012
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages40-49
Conference DateMay 16, 2012 - May 21, 2012
Conference PlaceBeijing, China
Indexed TypeEI
ISSN0302-9743
ISBN9783642299513
Department(1) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China; (2) School of Information Science and Engineering Graduate University of China Academy of Sciences Beijing China
English AbstractWe survey a recent new line of research on the small community phenomenon in networks, which characterizes the intuition and observation that in a broad class of networks, a significant fraction of nodes belong to some small communities. We propose the formal definition of this phenomenon as well as the definition of communities, based on which we are able to both study the community structure of network models, i.e., whether a model exhibits the small community phenomenon or not, and design new models that embrace this phenomenon in a natural way while preserving some other typical network properties such as the small diameter and the power law degree distribution. We also introduce the corresponding community detection algorithms, which not only are used to identify true communities and confirm the existence of the small community phenomenon in real networks but also have found other applications, e.g., the classification of networks and core extraction of networks. © 2012 Springer-Verlag.; We survey a recent new line of research on the small community phenomenon in networks, which characterizes the intuition and observation that in a broad class of networks, a significant fraction of nodes belong to some small communities. We propose the formal definition of this phenomenon as well as the definition of communities, based on which we are able to both study the community structure of network models, i.e., whether a model exhibits the small community phenomenon or not, and design new models that embrace this phenomenon in a natural way while preserving some other typical network properties such as the small diameter and the power law degree distribution. We also introduce the corresponding community detection algorithms, which not only are used to identify true communities and confirm the existence of the small community phenomenon in real networks but also have found other applications, e.g., the classification of networks and core extraction of networks. © 2012 Springer-Verlag.
SponsorshipState Key Laboratory of Computer Science; Chinese Academy of Sciences, Institute of Software; Chinese Academy of Sciences
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15731
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Peng Pan. the small community phenomenon in networks: models, algorithms and applications[C],2012:40-49.
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