Efficient processing of graph similarity queries with edit distance constraints

Abstract

Graphs are widely used to model complicated data semantics in many applications in bioinformatics, chemistry, social networks, pattern recognition, etc. A recent trend is to tolerate noise arising from various sources such as erroneous data entries and find similarity matches. In this paper, we study graph similarity queries with edit distance constraints… (More)
DOI: 10.1007/s00778-013-0306-1

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Citation Velocity: 13

Averaging 13 citations per year over the last 3 years.

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