Semi-supervised Clustering with Example Clusters

Celine Vens, Bart Verstrynge, Hendrik Blockeel

2013

Abstract

We consider the following problem: Given a set of data and one or more examples of clusters, find a clustering of the whole data set that is consistent with the given clusters. This is essentially a semi-supervised clustering problem, but different from those that have been studied until now. We argue that it occurs frequently in practice, but despite this, none of the existing methods can handle it well. We present a new method that specifically targets this type of problem. We show that the method works better than standard methods and identify opportunities for further improvement.

Paper Citation

in Harvard Style

Vens C., Verstrynge B. and Blockeel H. (2013). Semi-supervised Clustering with Example Clusters . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 45-51. DOI: 10.5220/0004547300450051

in Bibtex Style

@conference{kdir13,
author={Celine Vens and Bart Verstrynge and Hendrik Blockeel},
title={Semi-supervised Clustering with Example Clusters},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={45-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004547300450051},
isbn={978-989-8565-75-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - Semi-supervised Clustering with Example Clusters
SN - 978-989-8565-75-4
AU - Vens C.
AU - Verstrynge B.
AU - Blockeel H.
PY - 2013
SP - 45
EP - 51
DO - 10.5220/0004547300450051