Detecting cliques using degree and connectivity constraints

dc.contributor.author	Bhamaikar, A.A.
dc.contributor.author	Rao, P.R.
dc.date.accessioned	2015-06-04T03:23:54Z
dc.date.available	2015-06-04T03:23:54Z
dc.date.issued	2012
dc.identifier.citation	International Journal of Data Mining and Knowledge Management Process. 2; 2012; 39-46.	en_US
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/2746
dc.identifier.uri	http://aircconline.com/ijdkp/V2N2/2212ijdkp04.pdf
dc.description.abstract	In graph mining determining clique is np complete problem. This paper introduces pruning strategies, by which linear time algorithm for detecting clique is obtained. Clique determination is widely applicable in social network analysis. In social network analysis cliques signifies that each person in the network knows every other person in the group. Here pruning is done using edge connectivity and degree constraints. Initially the graph (g) is checked for a bridge, if it is detected, then graph (g) is disconnected. Then minimum and maximum degree criteria are used to determine a clique. The algorithm also has wide application in bioinformatics.
dc.publisher	AIRCC Publishing Corporation	en_US
dc.subject	Computer Science and Technology	en_US
dc.title	Detecting cliques using degree and connectivity constraints	en_US
dc.type	Journal article	en_US
dc.identifier.impf	y