1 |
S. V. N. Vishwanathan, N. N. Schraudolph, R. Kondor, and K. M. Borgwardt, "Graph kernels," Journal of Machine Learning Research, vol. 11, pp. 1201-1242, 2010.
|
2 |
D. Bu, Y. Zhao, L. Cai, H. Xue, X. Zhu, H. Lu, et al, "Topological structure analysis of the protein-protein interaction network in budding yeast," Nucleic Acids Research, vol. 31, no. 9, pp. 2443-2450, 2003.
DOI
|
3 |
R. Kumar, J. Novak, and A. Tomkins, "Structure and evolution of online social network," in Link Mining: Models, Algorithms, and Applications. New York, NY: Springer, 2010, pp. 337-357.
|
4 |
L. Tong, X. Zhou, and H. J. Miller, "Transportation network design for maximizing space-time accessibility," Transportation Research Part B: Methodological, vol. 81(Part 2), pp. 555-576, 2015.
DOI
|
5 |
Z. Zeng, A. K. H. Tung, J. Wang, J. Feng, and L. Zhou, "Comparing stars: on approximating graph edit distance," in Proceedings of the VLDB Endowment, vol. 2, no. 1, pp. 25-36, 2009.
DOI
|
6 |
W. Zheng, L. Zou, X. Lian, D. Wang, and D. Zhao, "Graph similarity search with edit distance constraint in large graph databases," in Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, San Francisco, CA, 2013, pp. 1595-1600.
|
7 |
X. Yan, F. Zhu, P. S. Yu, and J. Han, "Feature-based similarity search in graph structures," ACM Transactions on Database Systems (TODS), vol. 31, no. 4, pp. 1418-1453, 2006.
DOI
|
8 |
F. Hao, G. Min, Z. Pei, D. S. Park, and L. T. Yang, "k-Clique community detection in social networks based on formal concept analysis," IEEE Systems Journal, vol. 11, no. 1, pp. 250-259, 2017.
DOI
|
9 |
F. Hao, D. S. Park, G. Min, Y. S. Jeong, and J. H. Park, "k-Cliques mining in dynamic social networks based on triadic formal concept analysis," Neurocomputing, vol. 209, pp. 57-66, 2016.
DOI
|
10 |
F. Hao, S. S. Yau, G. Min, and L. T. Yang, "Detecting k-balanced trusted cliques in signed social networks," IEEE Internet Computing, vol. 18, no. 2, pp. 24-31, 2014.
DOI
|
11 |
H. Bunke, "On a relation between graph edit distance and maximum common subgraph," Pattern Recognition Letters, vol. 18, no. 8, pp. 689-694, 1997.
DOI
|
12 |
X. Gao, B. Xiao, D. Tao, and X. Li, "A survey of graph edit distance," Pattern Analysis and Applications, vol. 13, no. 1, pp. 113-129, 2010.
DOI
|
13 |
C. H. Elzinga and H. Wang, "Kernels for acyclic digraphs," Pattern Recognition Letters, vol. 33, no. 16, pp. 2239-2244, 2012.
DOI
|
14 |
B. Cao, Y. Li, and J. Yin, "Measuring similarity between graphs based on the Levenshtein distance," Applied Mathematics and Information Sciences, vol. 7, no. 1, pp. 169-175, 2013.
DOI
|
15 |
X. Wang and J. Ouyang, "A novel method to measure graph similarity," in Proceedings of the IEEE 12th International Conference on e-Business Engineering, Beijing, China, 2015, pp.180-185.
|
16 |
D. Koutra, J. T. Vogelstein, and C. Faloutsos, "DeltaCon: a principled massive-graph similarity function," in Proceedings of the 2013 SIAM International Conference on Data Mining, Austin, TX, 2013, pp. 162-170.
|
17 |
K. M. Borgwardt and H. P. Kriegel, "Shortest-path kernels on graphs," in Proceedings of the 5th IEEE International Conference on Data Mining, Houston, TX, 2005, pp. 74-81.
|
18 |
Y. Tian and J. M. Patel, "Tale: a tool for approximate large graph matching," in Proceedings of the 24th IEEE International Conference on Data Engineering, Cancun, Mexico, 2008, pp. 963-972.
|
19 |
F. Hao, D. S. Sim, and D. S. Park, "Measuring similarity between graphs based on formal concept analysis," in Proceedings of the 11th International Conference on Ubiquitous Information Technologies and Applications (CUTE 2016), Bangkok, Thailand, 2016, pp. 730-735.
|
20 |
F. Hao and S. Zhong, "Tag recommendation based on user interest lattice matching," in Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology, Chengdu, China, 2010, pp. 276-280.
|