@techreport{oai:ipsj.ixsq.nii.ac.jp:00186563,
 author = {Takashi, Horiyama and Masahiro, Miyasaka and Riku, Sasaki and Takashi, Horiyama and Masahiro, Miyasaka and Riku, Sasaki},
 issue = {7},
 month = {Mar},
 note = {In this paper, we focus on the isomorphism elimination. More precisely, our problem is as follows : Given a graph G with labeled edges and a family F of its subgraphs, we extract all automorphisms AutG = {π1, π2,...,} on the given graph, define the lexicographically largest subgraph for each set of the mutually isomorphic subgraphs on each automorphism πi, and select the lexicographically largest subgraphs on any of the automorphisms. In this paper, both of the given and resulting families of subgraphs are in the form of ZDDs, and the computation are performed on ZDDs. Experimental results show that the proposed method is 300 times faster and 3,000 times less memory than the conventional method in the best case., In this paper, we focus on the isomorphism elimination. More precisely, our problem is as follows : Given a graph G with labeled edges and a family F of its subgraphs, we extract all automorphisms AutG = {π1, π2,...,} on the given graph, define the lexicographically largest subgraph for each set of the mutually isomorphic subgraphs on each automorphism πi, and select the lexicographically largest subgraphs on any of the automorphisms. In this paper, both of the given and resulting families of subgraphs are in the form of ZDDs, and the computation are performed on ZDDs. Experimental results show that the proposed method is 300 times faster and 3,000 times less memory than the conventional method in the best case.},
 title = {Isomorphism Elimination by Zero-Suppressed Binary Decision Diagrams},
 year = {2018}
}