MONTE CARLO PROJECTIVE CLUSTERING OF TEXTS

Vladimír Ljubopytnov, Jaroslav Pokorný

2009

Abstract

In this paper we propose a new, improved version of a Monte Carlo projective clustering algorithm – DOC. DOC was designed for general vector data and we extend it to deal with variable dimension significance and use it in web search snippets clustering. We discuss advantages and weaknesses of our approach with respect to known algorithms.

Paper Citation

in Harvard Style

Ljubopytnov V. and Pokorný J. (2009). MONTE CARLO PROJECTIVE CLUSTERING OF TEXTS . In Proceedings of the 4th International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-989-674-010-8, pages 237-242. DOI: 10.5220/0002247602370242

in Bibtex Style

@conference{icsoft09,
author={Vladimír Ljubopytnov and Jaroslav Pokorný},
title={MONTE CARLO PROJECTIVE CLUSTERING OF TEXTS},
booktitle={Proceedings of the 4th International Conference on Software and Data Technologies - Volume 2: ICSOFT,},
year={2009},
pages={237-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002247602370242},
isbn={978-989-674-010-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Software and Data Technologies - Volume 2: ICSOFT,
TI - MONTE CARLO PROJECTIVE CLUSTERING OF TEXTS
SN - 978-989-674-010-8
AU - Ljubopytnov V.
AU - Pokorný J.
PY - 2009
SP - 237
EP - 242
DO - 10.5220/0002247602370242