Abstract
Locating source of information diffusion in networks has very important applications such as locating the sources of epidemics, news/rumors in social networks or online computer virus. In this paper, we consider detecting multiple rumor sources from a deterministic point of view by modeling it as the set resolving set (SRS) problem. Let G be a network on n nodes. A node subset K is an SRS of G if all detectable node sets are distinguishable by K. The problem of multiple rumor source detection (MRSD) in the network can be modeled as finding an SRS K with the smallest cardinality. In this paper, we propose a polynomial-time greedy algorithm for finding a minimum SRS in a general network, achieving performance ratio \(O(\ln n)\). This is the first work establishing a relation between the MRSD problem and a deterministic concept of SRS, and a first work to give the minimum SRS problem a polynomial-time performance-guaranteed approximation algorithm. Our framework suggests a robust and efficient approach for estimating multiple rumor sources independent of diffusion models in networks.
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Acknowledgments
This research is supported by NSFC (61222201,61472272), SRFDP (20126501110001), Xingjiang Talent Youth Project (2013711011).
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Zhang, Z., Xu, W., Wu, W. et al. A novel approach for detecting multiple rumor sources in networks with partial observations. J Comb Optim 33, 132–146 (2017). https://doi.org/10.1007/s10878-015-9939-x
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DOI: https://doi.org/10.1007/s10878-015-9939-x