A fast climbing approach for diffusion source inference in large social networks

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Abstract

In this era of information explosion, how to discover potential useful information in social networks and further locate the source has become of great importance. However, in front of the large scale social networks, the large calculation cost is the key difficulty in source locating algorithms. Aiming at this problem, we present a fast method based on climbing algorithms to locate the information source with less calculation cost in large scale social networks. Experimental results on both generated and real-world data sets show that our algorithm is more faster than existing algorithms, since it needs fewer iterations.

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Zang, W., Wang, X., Yao, Q., & Guo, L. (2015). A fast climbing approach for diffusion source inference in large social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9208, pp. 50–57). Springer Verlag. https://doi.org/10.1007/978-3-319-24474-7_8

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