TY - GEN
T1 - Indexing tree and subtree by using a structure network
AU - Zhang, Mingming
AU - Omachi, Shinichiro
PY - 2010
Y1 - 2010
N2 - In pattern recognition, graphs become alluring more and more as structural pattern representations due to their richer representability than feature vectors. However, there are many challenging problems using graphs for pattern recognition. One is that it is difficult to investigate the relationships of graphs effectively, even of trees. In this paper, we focus on the structure relationship analysis of trees, such as tree and subtree isomorphism, maximum common subtree, minimum common supertree, etc., which is almost suffered from all kinds of tree recognition problems. For investigating the relationships of structures of trees, we propose a structure network to represent the evolutional relationships of structures of trees. Moreover, for a lot of tree isomorphism problems appearing in the application of structure network, we propose a method that encodes the structure of tree as a numerical sequence, and illustrate its efficiency by comparing it with traditional matching method for tree isomorphism problem.
AB - In pattern recognition, graphs become alluring more and more as structural pattern representations due to their richer representability than feature vectors. However, there are many challenging problems using graphs for pattern recognition. One is that it is difficult to investigate the relationships of graphs effectively, even of trees. In this paper, we focus on the structure relationship analysis of trees, such as tree and subtree isomorphism, maximum common subtree, minimum common supertree, etc., which is almost suffered from all kinds of tree recognition problems. For investigating the relationships of structures of trees, we propose a structure network to represent the evolutional relationships of structures of trees. Moreover, for a lot of tree isomorphism problems appearing in the application of structure network, we propose a method that encodes the structure of tree as a numerical sequence, and illustrate its efficiency by comparing it with traditional matching method for tree isomorphism problem.
KW - structure analysis
KW - subtree isomorphism
KW - tree indexing
KW - tree isomorphism
KW - tree measure
UR - http://www.scopus.com/inward/record.url?scp=77958453956&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77958453956&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-14980-1_23
DO - 10.1007/978-3-642-14980-1_23
M3 - Conference contribution
AN - SCOPUS:77958453956
SN - 3642149790
SN - 9783642149795
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 244
EP - 253
BT - Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2010, Proceedings
T2 - 7th Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, SSPR and SPR 2010
Y2 - 18 August 2010 through 20 August 2010
ER -