Volume 12 Number 3 (May 2017)
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JCP 2017 Vol.12(3): 212-220 ISSN: 1796-203X
doi: 10.17706/jcp.12.3.212-220

Recommendation System for Criminal Behavioral Analysis on Social Network using Genetic Weighted K-Means Clustering

V. Soundarya1, U. Kanimozhi1, D. Manjula2
1Research Scholar, Department of Computer Science and Engineering, CEG, Anna University, Chennai-25, Tamil Nadu, India.
2 Department of Computer Science and Engineering, CEG, Anna University, Chennai-25, Tamil Nadu, India.


Abstract—The accessibility and usage of social networking sites constructs both prospects and menaces for the users. In this research article, we propose a new recommendation system for predicting and recommending the criminal behavioral users on social network based upon the activities of the users. Our recommender system uses the proposed nine factor analysis method, clustering technique called Genetic Weighted K-Means clustering (GWKMC) and the existing classification algorithm namely Negative Selection Algorithm (NSA). The proposed recommendation system is evaluated by conducting various experiments using the Face book dataset (Latest) which is prepared on our own and also the Weblog dataset (Timeworn). The conducted experiments confirmed the efficacy of the proposed Recommender System.

Index Terms—Criminal behavior, negative selection, recommendation system, weighted K-means clustering.

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Cite: V. Soundarya, U. Kanimozhi, D. Manjula, "Recommendation System for Criminal Behavioral Analysis on Social Network using Genetic Weighted K-Means Clustering," Journal of Computers vol. 12, no. 3, pp. 212-220, 2017.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Cherry L. Chen
Abstracting/ Indexing: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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