Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement

Mikio Mizukami, Kouich Hirata, Tetsuji Kuboyama

Abstract

In this paper, first we formulate the problem of a bipartite edge correlation clustering which finds an edge biclique partition with the minimum disagreement from a bipartite graph, by extending the bipartite correlation clustering which finds a biclique partition. Then, we design a simple randomized algorithm for bipartite edge correlation clustering, based on the randomized algorithm of bipartite correlation clustering. Finally, we give experimental results to evaluate the algorithms from both artificial data and real data.

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Paper Citation


in Harvard Style

Mizukami M., Hirata K. and Kuboyama T. (2019). Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 699-706. DOI: 10.5220/0007471506990706


in Bibtex Style

@conference{icpram19,
author={Mikio Mizukami and Kouich Hirata and Tetsuji Kuboyama},
title={Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={699-706},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007471506990706},
isbn={978-989-758-351-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Bipartite Edge Correlation Clustering: Finding an Edge Biclique Partition from a Bipartite Graph with Minimum Disagreement
SN - 978-989-758-351-3
AU - Mizukami M.
AU - Hirata K.
AU - Kuboyama T.
PY - 2019
SP - 699
EP - 706
DO - 10.5220/0007471506990706