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- W2337692797 abstract "Graphs are widely employed in many application fields, such as biology, chemistry, social networks, databases and so on. Graphs allow to describe a set of objects together with their relationships.Analysing these data often requires to measure the similarity between two graphs. Unfortunately, due to its combinatorial nature, this is a NP-Complete problem generally addressed using different kind of heuristics.In this Thesis we have explored two approaches to compute the similarity between graphs. The former is based on the exact graph matching approach. We have designed, VF3, an algorithm aimed to search for pattern structures within graphs. While, the second approach is an inexact graph matching method which aims to compute an efficient approximation of the Graph Edit Distance (GED) as a Quadratic Assignment Problem (QAP)." @default.
- W2337692797 created "2016-06-24" @default.
- W2337692797 creator A5043110356 @default.
- W2337692797 date "2016-01-01" @default.
- W2337692797 modified "2023-09-23" @default.
- W2337692797 title "Exacts and Inexacts methods for graph similarity in Structural Pattern Recognition" @default.
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- W2337692797 hasPublicationYear "2016" @default.
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