Exact and Inexact Methods for Graph Similarity in Structural Pattern Recognition PhD thesis of Vincenzo Carletti.

Vincenzo Carletti 1, 2
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
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).
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Submitted on : Friday, May 13, 2016 - 3:34:10 PM
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Vincenzo Carletti. Exact and Inexact Methods for Graph Similarity in Structural Pattern Recognition PhD thesis of Vincenzo Carletti.. Computer Vision and Pattern Recognition [cs.CV]. Université de Caen; Universita degli studi di Salerno, 2016. English. ⟨tel-01315389⟩

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