loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: João M. M. Duarte 1 ; Ana L. N. Fred 2 and F. Jorge Duarte 1

Affiliations: 1 Instituto Superior de Engenharia do Porto, Instituto Superior Politécnico, Portugal ; 2 Instituto Superior Técnico, Portugal

Abstract: Recent work has focused the incorporation of a priori knowledge into the data clustering process, in the form of pairwise constraints, aiming to improve clustering quality and find appropriate clustering solutions to specific tasks or interests. In this work, we integrate must-link and cannot-link constraints into the cluster ensemble framework. Two algorithms for combining multiple data partitions with instance level constraints are proposed. The first one consists of a modification to Evidence Accumulation Clustering and the second one maximizes both the similarity between the cluster ensemble and the target consensus partition, and constraint satisfaction using a genetic algorithm. Experimental results shown that the proposed constrained clustering combination methods performances are superior to the unconstrained Evidence Accumulation Clustering.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.221.59.121

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Duarte, J.; Fred, A. and Duarte, F. (2009). Combining Data Clusterings with Instance Level Constraints. In Proceedings of the 9th International Workshop on Pattern Recognition in Information Systems (ICEIS 2009) - PRIS; ISBN 978-989-8111-89-0, SciTePress, pages 49-60. DOI: 10.5220/0002260300490060

@conference{pris09,
author={João M. M. Duarte. and Ana L. N. Fred. and F. Jorge Duarte.},
title={Combining Data Clusterings with Instance Level Constraints},
booktitle={Proceedings of the 9th International Workshop on Pattern Recognition in Information Systems (ICEIS 2009) - PRIS},
year={2009},
pages={49-60},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002260300490060},
isbn={978-989-8111-89-0},
}

TY - CONF

JO - Proceedings of the 9th International Workshop on Pattern Recognition in Information Systems (ICEIS 2009) - PRIS
TI - Combining Data Clusterings with Instance Level Constraints
SN - 978-989-8111-89-0
AU - Duarte, J.
AU - Fred, A.
AU - Duarte, F.
PY - 2009
SP - 49
EP - 60
DO - 10.5220/0002260300490060
PB - SciTePress