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Community Kernels Detection in OSN using SVM Clustering and Classification

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 113 - Number 11
Year of Publication: 2015
Authors:
Rahul Nema
Anjana Pandey
10.5120/19869-1854

Rahul Nema and Anjana Pandey. Article: Community Kernels Detection in OSN using SVM Clustering and Classification. International Journal of Computer Applications 113(11):9-13, March 2015. Full text available. BibTeX

@article{key:article,
	author = {Rahul Nema and Anjana Pandey},
	title = {Article: Community Kernels Detection in OSN using SVM Clustering and Classification},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {113},
	number = {11},
	pages = {9-13},
	month = {March},
	note = {Full text available}
}

Abstract

Security is an important issue in online social networking web sites. Here in OSN users can post their messages publicly on wall. In OSN a person may be attached to a community and can post any message on their friend's wall, hence it is necessary to check the validity of the user in the communities. Although there are various techniques implemented for the detection of community kernels in OSN. Here in this paper a new and efficient technique for the detection of community kernels in large OSN using combinatorial method of support vector machine based clustering and classification of Community kernels in the dataset is proposed. The proposed technique implemented provides high precision and recall as compared to the existing technique of Greedy and WEBA.

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