Multi-Objective Optimization in Social Networks: A Knowledge-Driven Computational Approach

This presentation begins by reviewing the fundamentals and key characteristics of social networks, along with primary challenges such as community detection, link prediction, and influence maximization. We then explore how these problems can be framed as multi-objective optimization tasks that require balancing multiple goals simultaneously. To address these problems, a knowledge-driven computational approach is presented that guides the optimization process by leveraging various sources of knowledge extracted from the network structure. Finally, we discuss the effectiveness of this approach in handling the complex and dynamic nature of social <a href="http://networks.

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Speaker(s): Pooya Moradian Zadeh

Bldg: School of Computer Science, Advanced Computing Hub, 4th Floor, 300 Ouellette Ave., Windsor, Ontario, Canada