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Authors: Huaying Li and Aleksandar Jeremic

Affiliation: McMaster University, Canada

ISBN: 978-989-758-069-7

Keyword(s): Clustering, Information Fusion, Cluster Ensemble and Semi-supervised Learning.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Biometrics ; Biometrics and Pattern Recognition ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing ; Multimedia ; Multimedia Signal Processing ; Pattern Recognition ; Telecommunications

Abstract: Clustering analysis is a widely used technique to find hidden patterns of a data set. Combining multiple clustering results into a consensus clustering (cluster ensemble) is a popular and efficient method to improve the quality of clustering analysis. Many algorithms were proposed in the literature and most of which are unsupervised learning techniques. In this paper, we proposed a semi-supervised cluster ensemble algorithm. It is so-called semi-supervised because labels of some data points in the given data set are known or provided by experts. To evaluate the performance of the proposed algorithm, we compare it with other well-known algorithms, such as MCLA and BCE.

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Paper citation in several formats:
Li, H. and Jeremic, A. (2015). Information Fusion for Semi-supervised Cluster Labelings.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015) ISBN 978-989-758-069-7, pages 318-323. DOI: 10.5220/0005282203180323

@conference{biosignals15,
author={Huaying Li. and Aleksandar Jeremic.},
title={Information Fusion for Semi-supervised Cluster Labelings},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)},
year={2015},
pages={318-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005282203180323},
isbn={978-989-758-069-7},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)
TI - Information Fusion for Semi-supervised Cluster Labelings
SN - 978-989-758-069-7
AU - Li, H.
AU - Jeremic, A.
PY - 2015
SP - 318
EP - 323
DO - 10.5220/0005282203180323

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