Abstract: In this study, we introduce a novel approach to influence optimization in social networks by leveraging the mathematical framework of hypergraphs.
Abstract. In this study, we introduce a novel approach to influence optimization in social networks by leveraging the mathematical framework of hypergraphs.
Navigating Social Networks: A Hypergraph Approach to Influence Optimization. Authors: Murali K. Enduri. Abstract: In this study, we introduce a novel approach ...
Jun 23, 2021 · This study generalizes the TSS problem on networks characterized by many-to-many relationships modeled via hypergraphs.
Navigating Social Networks: A Hypergraph Approach to Influence Optimization · M. Enduri. Computer Science, Mathematics. International Conference on Complex ...
Influence maximization aims to select a set of influential nodes from the online social network to maximize the influence spread based on a given information ...
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In this approach, the information extracted from social networks transcends cohesive groups, enabling the discovery of brokers that interact among communities.
In this paper, we first propose the Crowd-LT model for hypergraph, which integrates bandwagon effect from psychology. Then the framework of Influence ...
Jan 17, 2023 · In this chapter, we introduce three typical applications of hypergraph computation, ie, recommender system, sentiment analysis, and emotion recognition.
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Navigating Social Networks: A Hypergraph Approach to Influence Optimization · M. Enduri. Computer Science, Mathematics. International Conference on Complex ...