Abstract
Community structure detection is an important study in social network analysis, especially with complex networks. In a community structure, usually, a node belongs to only one community. In reality, however, networks are built in different relationships and nodes can be shared by multiple communities. An overlapping node is a vertex that belongs to more than one community. The concept of overlapping community has emerged and has great practical significance for applications on social networks. To detect, analyze or process overlapping communities, many soft algorithms (probability-based computation, giving acceptable results…) are proposed to perform. In this study, we introduce the tool “Maximum Likelihood Estimation-MLE, a commonly used tool in machine learning, then apply Gradient descent to calculate the extrema for the proposed objective function. The experimental results prove the flexibility and effectiveness of the proposed method, which is good support for further studies on social network analysis and graph data mining.
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Trinh, N.H., Tung, C.T. (2023). Processing Overlapping Communities Using the Gradient Descent Optimization Method. In: Nghia, P.T., Thai, V.D., Thuy, N.T., Son, L.H., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2023. Lecture Notes in Networks and Systems, vol 847. Springer, Cham. https://doi.org/10.1007/978-3-031-49529-8_31
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DOI: https://doi.org/10.1007/978-3-031-49529-8_31
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