Self-organizing graph edit distance

被引：0

作者：

Neuhaus, M ^{[1
]}

Bunke, H ^{[1
]}

机构：

[1] Univ Bern, Dept Comp Sci, CH-3012 Bern, Switzerland

来源：

GRAPH BASED REPRESENTATIONS IN PATTERN RECOGNITION, PROCEEDINGS | 2003年 / 2726卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper addresses the issue of learning graph edit distance cost functions for numerically labeled graphs from a corpus of sample graphs. We propose a system of self-organizing maps representing attribute distance spaces that encode edit operation costs. The self-organizing maps are iteratively adapted to minimize the edit distance of those graphs that are required to be similar. To demonstrate the learning effect, the distance model is applied to graphs representing line drawings and diatoms.

引用

页码：83 / 94

页数：12

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