Genetic operators for hierarchical graph clustering

In this paper we propose an encoding scheme and ad hoc operators for a genetic approach to hierarchical graph clustering. Given a connected graph whose vertices correspond to points within a Euclidean space and a fitness function, a hierarchy of graphs in which each vertex corresponds to a connected...

Full description

Saved in:
Bibliographic Details
Published inPattern recognition letters Vol. 19; no. 14; pp. 1293 - 1300
Main Author Rizzi, Stefano
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.12.1998
Subjects
Autonomous robots
Euclidean graphs
Genetic algorithms
Hierarchical clustering
Euclidean graphs
Hierarchical clustering
Genetic algorithms
Autonomous robots
Online AccessGet full text

Cover

More Information
Summary:In this paper we propose an encoding scheme and ad hoc operators for a genetic approach to hierarchical graph clustering. Given a connected graph whose vertices correspond to points within a Euclidean space and a fitness function, a hierarchy of graphs in which each vertex corresponds to a connected subgraph of the graph below is generated. Both the number of clustering levels and the number of clusters on each level are not fixed a priori and are subject to optimization.
ISSN:0167-8655
1872-7344
DOI:10.1016/S0167-8655(98)00110-X