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ACMSE
2005
ACM
14 years 1 months ago
Bibliometric approach to community discovery
Recent research suggests that most of the real-world random networks organize themselves into communities. Communities are formed by subsets of nodes in a graph, which are closely...
Narsingh Deo, Hemant Balakrishnan
ESANN
2003
13 years 9 months ago
Modeling of growing networks with directional attachment and communities
In this paper, we propose a new network growth model and its learning algorithm to more precisely model such a real-world growing network as the Web. Unlike the conventional model...
Masahiro Kimura, Kazumi Saito, Naonori Ueda
WEBI
2010
Springer
13 years 5 months ago
Discovering Research Communities by Clustering Bibliographical Data
Today's world is characterized by the multiplicity of interconnections through many types of links between the people, that is why mining social networks appears to be an impo...
Fabrice Muhlenbach, Stéphane Lallich
KCAP
2005
ACM
14 years 1 months ago
CORDER: COmmunity relation discovery by named entity recognition
We present a text mining method called CORDER [4] which discovers social networks from an organization’s documents. CORDER finds relations between a target named entity and othe...
Jianhan Zhu, Alexandre L. Gonçalves, Victor...
ISCIS
2005
Springer
14 years 1 months ago
Computing Communities in Large Networks Using Random Walks
Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Computing them however is generally expe...
Pascal Pons, Matthieu Latapy