The approximate graph matching problem

Jason T.L. Wang, Kaizhong Zhang, Gung Wei Chirn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

Labeled graphs are graphs in which each node and edge has a label. The distance between two labeled graphs is considered to be the weighted sum of the costs of edit operations (insert, delete and relabel the nodes and edges) to transform one graph to the other. The paper considers two variants of the approximate graph matching problem (AGM): Given a pattern graph P and a data graph D, what is the distance between P and D ? What is the minimum distance between P and D when subgraphs can be freely removed from D ? We show that no efficient algorithm can solve either variant of the AGM, unless P = NP. We then give a polynomial-time approximation algorithm to solve this problem.

Original languageEnglish (US)
Title of host publicationProceedings of the 12th IAPR International Conference on Pattern Recognition - Conference B
Subtitle of host publicationPattern Recognition and Neural Networks, ICPR 1994
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages284-288
Number of pages5
ISBN (Electronic)0818662700
StatePublished - 1994
Event12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994 - Jerusalem, Israel
Duration: Oct 9 1994Oct 13 1994

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Conference

Conference12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994
Country/TerritoryIsrael
CityJerusalem
Period10/9/9410/13/94

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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