Abstract
In analysis of ubiquitous networks, one critical work is to understand the internal structure of the networks. Many approaches are proposed to address the structure mining in the graph. Unfortunately, these approaches cannot cope with the big graph generated by large-scale streaming data. Aiming to mine the structure from the big graph, this paper presents an efficient mining framework, namely cSketch, which is used for capturing the cliques from big graph quickly. Two illustrative examples are conducted for demonstrating the feasibility and effectiveness of the proposed framework.
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Acknowledgements
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-2014-0-00720) supervised by the IITP (Institute for Information and Communications Technology Promotion) and the National Research Foundation of Korea (No. NRF-2017R1A2B1008421) and partly supported by the Fundamental Research Funds for the Central Universities, China (No. GK201703059) and Shanxi Scholarship Council of China (No. 2015-068).
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Hao, F., Park, DS. cSketch: a novel framework for capturing cliques from big graph. J Supercomput 74, 1202–1214 (2018). https://doi.org/10.1007/s11227-017-2114-7
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DOI: https://doi.org/10.1007/s11227-017-2114-7