Volume 11 Number 1 (Jan. 2016)
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JCP 2016 Vol.11(1): 18-25 ISSN: 1796-203X
doi: 10.17706/jcp.11.1.18-25

A Particle Swarm Optimization Based Approach for Finding Similar Users on Facebook

Pratik S. Kabara, Vishal Kaushal, Akshay Divekar, Mohit Kamdar, Devvrat Ganeriwal
Department of Computer Engineering, Vishwakarma Institute of Technology Pune, Maharashtra, India.
Abstract—With ever increasing size and use of social networks, there is a large amount of information which users implicitly or explicitly leave behind on social media. This information can be used to identify their personal traits and preferences. In this work, we have proposed a Particle Swarm Optimization (PSO) based approach for clustering users on Facebook (FB) data to identify similar users. Proposed method can be used to recommend people having similar interests. Our results indicate a lesser quantization error than k-means when used for 7 or less clusters. Possible applications of this approach include rope-in exercises for new hires, assigning a resource person to work team, etc.

Index Terms—Clustering method, facebook, particle swarm optimization (PSO), recommender systems, social network services.

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Cite: Pratik S. Kabara, Vishal Kaushal, Akshay Divekar, Mohit Kamdar, Devvrat Ganeriwal, "A Particle Swarm Optimization Based Approach for Finding Similar Users on Facebook," Journal of Computers vol. 11, no. 1, pp. 18-25, 2016.

General Information

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