This paper proposes a new evolutionary algorithm for subspace clustering in very large and high dimensional databases. The design includes task-specific coding and genetic operators, along with a non-random initialization procedure. Reported experimental results show the algorithm scales almost linearly with the size and dimensionality of the database as well as the dimensionality of the hidden clusters.
Description
Towards Effective Subspace Clustering with an Evolutionary Algorithm
%0 Conference Paper
%1 Computer03towardseffective
%A Computer, Ioannis Sarafis
%A Sarafis, Ioannis A.
%A Trinder, Phil W.
%A Zalzala, Ali M. S.
%B in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC’03
%D 2003
%K 2009 clustering seminar
%T Towards Effective Subspace Clustering with an Evolutionary Algorithm
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.1512
%X This paper proposes a new evolutionary algorithm for subspace clustering in very large and high dimensional databases. The design includes task-specific coding and genetic operators, along with a non-random initialization procedure. Reported experimental results show the algorithm scales almost linearly with the size and dimensionality of the database as well as the dimensionality of the hidden clusters.
@inproceedings{Computer03towardseffective,
abstract = {This paper proposes a new evolutionary algorithm for subspace clustering in very large and high dimensional databases. The design includes task-specific coding and genetic operators, along with a non-random initialization procedure. Reported experimental results show the algorithm scales almost linearly with the size and dimensionality of the database as well as the dimensionality of the hidden clusters.},
added-at = {2009-11-12T15:48:29.000+0100},
author = {Computer, Ioannis Sarafis and Sarafis, Ioannis A. and Trinder, Phil W. and Zalzala, Ali M. S.},
biburl = {https://www.bibsonomy.org/bibtex/28f79a52a5f18f8d3f11485b0b59c29b2/k.e.},
booktitle = {in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC’03},
description = {Towards Effective Subspace Clustering with an Evolutionary Algorithm},
interhash = {483fd442bc4d0b185cf61074eedb06f5},
intrahash = {8f79a52a5f18f8d3f11485b0b59c29b2},
keywords = {2009 clustering seminar},
timestamp = {2009-11-12T15:48:29.000+0100},
title = {Towards Effective Subspace Clustering with an Evolutionary Algorithm},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.1512},
year = 2003
}