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Improved Lower Bounds for Graph Edit Distance.

Authors :
Blumenthal, David B.
Gamper, Johann
Source :
IEEE Transactions on Knowledge & Data Engineering; Mar2018, Vol. 30 Issue 3, p503-516, 14p
Publication Year :
2018

Abstract

The problem of deriving lower and upper bounds for the edit distance between undirected, labeled graphs has recently received increasing attention. However, only one algorithm has been proposed that allegedly computes not only an upper but also a lower bound for non-uniform edit costs and incorporates information about both node and edge labels. In this paper, we demonstrate that this algorithm is incorrect. We present a corrected version \mathsf B\scriptstyleRANCH<alternatives> <inline-graphic xlink:href="blumenthal-ieq1-2772243.gif"/></alternatives> that runs in \mathcalO(n^2\Delta ^3+n^3)<alternatives> <inline-graphic xlink:href="blumenthal-ieq2-2772243.gif"/></alternatives> time, where \Delta<alternatives><inline-graphic xlink:href="blumenthal-ieq3-2772243.gif"/> </alternatives> is the maximum of the maximum degrees of input graphs G<alternatives><inline-graphic xlink:href="blumenthal-ieq4-2772243.gif"/> </alternatives> and H<alternatives> <inline-graphic xlink:href="blumenthal-ieq5-2772243.gif"/></alternatives>. We also develop a speed-up <alternatives><inline-graphic xlink:href="blumenthal-ieq6-2772243.gif"/></alternatives> that runs in \mathcal{O}(n^2\Delta ^2+n^3)<alternatives> <inline-graphic xlink:href="blumenthal-ieq7-2772243.gif"/></alternatives> time and computes an only slightly less accurate lower bound. The lower bounds produced by \mathsf B\scriptstyleRANCH<alternatives><inline-graphic xlink:href="blumenthal-ieq8-2772243.gif"/> </alternatives> and \mathsf {B\scriptstyle{RANCH}}\mathsf{F\scriptstyle{AST}}<alternatives> <inline-graphic xlink:href="blumenthal-ieq9-2772243.gif"/></alternatives> are shown to be pseudo-metrics on a collection of graphs. Finally, we suggest an anytime algorithm \mathsf B\scriptstyleRANCH\mathsfT\scriptstyleIGHT<alternatives> <inline-graphic xlink:href="blumenthal-ieq10-2772243.gif"/></alternatives> that iteratively improves \mathsf B\scriptstyleRANCH<alternatives> <inline-graphic xlink:href="blumenthal-ieq11-2772243.gif"/></alternatives>’s lower bound. \mathsf B\scriptstyleRANCH\mathsfT\scriptstyleIGHT <alternatives><inline-graphic xlink:href="blumenthal-ieq12-2772243.gif"/></alternatives> runs in \mathcalO(n^3\Delta ^2+I(n^2\Delta ^3+n^3))<alternatives> <inline-graphic xlink:href="blumenthal-ieq13-2772243.gif"/></alternatives> time, where the number of iterations $I$<alternatives> <inline-graphic xlink:href="blumenthal-ieq14-2772243.gif"/></alternatives> is controlled by the user. A detailed experimental evaluation shows that all suggested algorithms are Pareto optimal, that they are very effective when used as filters for edit distance range queries, and that they perform excellently when used within classification frameworks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10414347
Volume :
30
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Knowledge & Data Engineering
Publication Type :
Academic Journal
Accession number :
127814368
Full Text :
https://doi.org/10.1109/TKDE.2017.2772243