DocumentCode :
133931
Title :
Detecting community structure based on traffic at node in networks
Author :
Sihag, V.K. ; Anand, Abhineet ; Tomar, Ravi ; Chandra, Jagdish ; Tiwari, Rajeev ; Dumka, Ankur ; Poonia, A.S.
Author_Institution :
Sardar Patel Univ. of Police, Vallabh Vidyanagar, India
fYear :
2014
fDate :
1-2 March 2014
Firstpage :
1
Lastpage :
9
Abstract :
In the study of networks, such as complex network, social network or biological network; number of different characteristics of many nodes are found common. These characteristics includes small-world property, clustering and community structure, among others. In the context of networks, community structure refers to occurrence of groups of nodes in a network that are more densely connected internally, then with the rest of network. This heterogeneity of connection suggests that network has certain natural division within it. Being able to identify their sub-structure within the network can provide inside into how network function and topology affects each others.
Keywords :
computational complexity; graph theory; network theory (graphs); pattern clustering; small-world networks; biological network; clustering characteristics; community structure detection; complex network; computational complexity; connection heterogeneity; network function; network node traffic; network substructure; network topology; node groups; small-world property; social network; Clustering algorithms; Communities; Complex networks; Complexity theory; Image edge detection; Program processors; Social network services; Activity Recognition; Acyclic Directed Graphs; Bayesian Networks; Customer Service; Digital Forensics; Live data acquisition; Online Commercial Intention; Social Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical, Electronics and Computer Science (SCEECS), 2014 IEEE Students' Conference on
Conference_Location :
Bhopal
Print_ISBN :
978-1-4799-2525-4
Type :
conf
DOI :
10.1109/SCEECS.2014.6804502
Filename :
6804502
Link To Document :
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