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Social Network Analysis Using Evolutionary Computations

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  • Fri, 11/24/2017 - 10:00am - 12:00pm


PhD. Comprehensive Exam by:

Kalyani Selvarajah

Date: Friday, November 24th, 2017
Time: 10:00 am - 12:00 pm
Location: LT 3105

Abstract: Social network analysis (SNA) says the story of social structure and how the social actors are interconnected together. It is an alternative way to investigate the complex social system of billions of connected components. In this complex system, how can we successfully collaborate collection of intelligent to provide productive results to the world. The inherent dynamic nature of large-scale social network makes it difficult. Therefore, to address this issue, although many models are existing with significant improvements, still it needs a computationally efficient design. In artificial intelligence, evolutionary computation is a problem-solving technique based on the principles of biological evolutions.  So, incorporating evolutionary computing into SNA will be an effective way to analyze the problems. This presentation will deliver the background of social network analysis, its current issues, fundamental to evolutionary computation and its application in SNA.

Thesis Committee:    
Internal Reader: Dr. Robert Kent and Dr. Saeed Samet      
External Reader: Dr. Kathy Pfaff
Advisor: Dr. Ziad Kobti
Co-Supervisor: Dr. Mehdi Kargar

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