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Journal ArticleDOI

A survey of graph edit distance

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TLDR
The research advance of G ED is surveyed in order to provide a review of the existing literatures and offer some insights into the studies of GED.
Abstract
Inexact graph matching has been one of the significant research foci in the area of pattern analysis. As an important way to measure the similarity between pairwise graphs error-tolerantly, graph edit distance (GED) is the base of inexact graph matching. The research advance of GED is surveyed in order to provide a review of the existing literatures and offer some insights into the studies of GED. Since graphs may be attributed or non-attributed and the definition of costs for edit operations is various, the existing GED algorithms are categorized according to these two factors and described in detail. After these algorithms are analyzed and their limitations are identified, several promising directions for further research are proposed.

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Citations
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Graph-based Anomaly Detection and Description: A Survey

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A Survey on Metric Learning for Feature Vectors and Structured Data

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Book ChapterDOI

Graph R-CNN for Scene Graph Generation

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Journal ArticleDOI

Graph matching and learning in pattern recognition in the last 10 years

TL;DR: This paper examines the main advances registered in the last ten years in Pattern Recognition methodologies based on graph matching and related techniques, analyzing more than 180 papers.
References
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Journal ArticleDOI

A note on two problems in connexion with graphs

TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
Book

Self-Organizing Maps

TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
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