Abstract
Graph, an important information organizational structure, is commonly used for representing the social networks, web, and other internet applications. This paper tackles a fundamental problem on measuring similarity between graphs that is the essential step for graph searching, matching, pattern discovery. To efficiently measure the similarity between graphs, this paper pioneers a novel approach for measurement of similarity between graphs by using formal concept analysis that can clearly describe the relationships between nodes. A case study is provided for demonstrating the feasibility of the proposed approach.
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Acknowledgments
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) (IITP-2015-IITP-2015-H8601-15-1009) supervised by the IITP (Institute for Information & communications Technology Promotion) and Basic Science Research program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF-2014R1A1A4A01007190).
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Hao, F., Sim, DS., Park, DS. (2017). Measuring Similarity Between Graphs Based on Formal Concept Analysis. In: Park, J., Pan, Y., Yi, G., Loia, V. (eds) Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016 2016 2016. Lecture Notes in Electrical Engineering, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-10-3023-9_112
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DOI: https://doi.org/10.1007/978-981-10-3023-9_112
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