Abstract
Complex networking analysis is a powerful technique for understanding both complex networks and big graphs in ubiquitous computing. Particularly, there are several novel metrics, such as k-clique and k-core are proposed in order to study the relative importance of nodes in complex networks. Among of those metrics, k-core analysis is an effective approach for simplifying graphical structure. However, the relation between k and the scale of networks is not explored in most existing literature. Toward this end, this paper formulate a new research problem, \(\theta\)-Iceberg Core decomposition in graphs, which is able to incorporate a parameter \(\theta\) (\(0<\theta \le 1\)) used for relaxing the output of k-cores. Further, we propose a formal concept analysis based approach for \(\theta\)-Iceberg Core decomposition. The proposed approach and its conclusions can provide theoretical basis and guidance for the potential applications of \(\theta\)-Iceberg Core analysis in complex networks.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (Grant No. 61702317, 61771297) and 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 & communications Technology Promotion) and the National Research Foundation of Korea (No. NRF-2017R1A2B1008421) and was also supported by the Fundamental Research Funds for the Central Universities (GK201703059, GK201703054).
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Hao, F., Xinchang, K. & Park, DS. FCA-based \(\theta\)-iceberg core decomposition in graphs. J Ambient Intell Human Comput 15, 1423–1428 (2024). https://doi.org/10.1007/s12652-017-0649-3
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DOI: https://doi.org/10.1007/s12652-017-0649-3