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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Tang, J., Chang, Y., Aggarwal, C., Liu, H.: A survey of signed network mining in social media. ACM Comput. Surv. 49(3), 42 (2016)
Khodadadi, A., Jalili, M.: Sign prediction in social networks based on tendency rate of equivalent micro-structures. Neurocomputing 257, 175–184 (2017)
Lu, C., Yu, J.X., Li, R.-H., Wei, H.: Exploring hierarchies in online social networks. IEEE Trans. Knowl. Data Eng. 28(8), 2086–2100 (2016)
Wu, Z., Aggarwal, C.C., Sun, J.: The troll-trust model for ranking in signed networks. In: Proceeding of 9th ACM International Conference on Web Search Data Mining, pp. 447–456 (2016)
Cartwright, D., Harary, F.: Structural balance: a generalization of Heider’s theory. Psychol. Rev. 63(5), 277 (1956)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. SSS, Springer, New York (2009). https://doi.org/10.1007/978-0-387-84858-7
Kumar, S., Spezzano, F., Subrahmanian, V., Faloutsos, C.: Edge weight prediction in weighted signed networks. In: 2016 IEEE 16th International Conference on Data Mining, ICDM, pp. 221–230. IEEE (2016)
Massa, P., Avesani, P.: Trust-aware recommender systems. In: Proceedings of the 2007 ACM Conference on Recommender Systems, pp. 7–24 (2007)
Nguyen, D.Q.N., Xing, L., Lin, L.: Weight prediction for variants of weighted directed networks. In: 2020 IEEE International Conference on Big Data (2020)
Nguyen, D.Q.N., Xing, L., Lin, L.: Community detection, pattern recognition, and hypergraph-based learning: approaches using metric geometry and persistent homology. In: Fuzzy Systems and Data Mining VI, Proceedings of Frontiers in Artificial Intelligence and Applications, pp. 457–473 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-031-10464-0_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-10463-3
Online ISBN: 978-3-031-10464-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)