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Author: Giulio Genovese

Affiliation: Dartmouth College, United States

Abstract: A new agglomerative algorithm is introduced that can be used as a replacement for any partitioning algorithm that tries to optimize an objective function related to graph cuts. In particular, spectral clustering algorithms fall in this category. A new measure of similarity is introduced to show that the approach, although radically different from the one adopted in partitioning approaches, tries to optimize the same objective. Experiments are performed for the problem of image segmentation but the idea can be applied to a broader range of applications.

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Paper citation in several formats:
Genovese, G. (2008). Weighted Agglomerative Clustering to Solve Normalized Cuts Problems. In Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - PRIS, (ICEIS 2008) ISBN 978-989-8111-42-5, pages 67-76. DOI: 10.5220/0001740100670076

@conference{pris08,
author={Giulio Genovese.},
title={Weighted Agglomerative Clustering to Solve Normalized Cuts Problems},
booktitle={Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - PRIS, (ICEIS 2008)},
year={2008},
pages={67-76},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001740100670076},
isbn={978-989-8111-42-5},
}

TY - CONF

JO - Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - PRIS, (ICEIS 2008)
TI - Weighted Agglomerative Clustering to Solve Normalized Cuts Problems
SN - 978-989-8111-42-5
AU - Genovese, G.
PY - 2008
SP - 67
EP - 76
DO - 10.5220/0001740100670076

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