Physics Simulation Based Approach to Node Clustering
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-2300-5_15
Reference15 articles.
1. Aggarwal, C.C., Wang, H.: A Survey of Clustering Algorithms for Graph Data, pp. 275–301. Springer US, Boston, MA (2010). https://doi.org/10.1007/978-1-4419-6045-0_9
2. Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: Membership, growth, and evolution. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 44–54. Association for Computing Machinery (2006). https://doi.org/10.1145/1150402.1150412
3. Bellman, R., Bellman, R., Collection, K.M.R.: Adaptive Control Processes: A Guided Tour. Princeton Legacy Library, Princeton University Press (1961). https://books.google.co.in/books?id=POAmAAAAMAAJ
4. Campello, R.J.G.B., Moulavi, D., Sander, J.: Density-based clustering based on hierarchical density estimates. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds.) Advances in Knowledge Discovery and Data Mining, pp. 160–172. Springer, Berlin, Heidelberg (2013)
5. Diestel, R.: Graph Theory, 4th Edition, Graduate texts in mathematics, vol. 173. Springer (2012)
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