Abstract
In this paper, we propose a new SVM method for predicting signs of edges in weighted and signed networks. Our method is based on the notions of dual-graph operation and filtered neighborhoods of nodes in dual graphs, which allows to introduce a geometric structure on the set of nodes of dual graphs and lead to a modified SVM method for predicting edge signs in weighted and signed networks. We test our method on several real datasets.
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Le, P.D.T., Nguyen, N.N.N., Nguyen, D.Q.N. (2022). An Adaptive Geometry and Dual Graph Approach to Sign Prediction for Weighted and Signed Networks. In: Arai, K. (eds) Intelligent Computing. SAI 2022. Lecture Notes in Networks and Systems, vol 507. Springer, Cham. https://doi.org/10.1007/978-3-031-10464-0_1
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DOI: https://doi.org/10.1007/978-3-031-10464-0_1
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