loading
Documents

Research.Publish.Connect.

Paper

Authors: Nabil El malki 1 ; Franck Ravat 2 and Olivier Teste 3

Affiliations: 1 Université de Toulouse, UT2, IRIT(CNRS/UMR5505), Toulouse, France, Capgemini, 109 Avenue du Général Eisenhower, Toulouse and France ; 2 Université de Toulouse, UT2, IRIT(CNRS/UMR5505), Toulouse and France ; 3 Capgemini, 109 Avenue du Général Eisenhower, Toulouse and France

ISBN: 978-989-758-372-8

Keyword(s): k-means, Machine Learning, Data Aggregations.

Abstract: The k-means algorithm is one well-known of clustering algorithms. k-means requires iterative and repetitive accesses to data up to performing the same calculations several times on the same data. However, intermediate results that are difficult to predict at the beginning of the k-means process are not recorded to avoid recalculating some data in subsequent iterations. These repeated calculations can be costly, especially when it comes to clustering massive data. In this article, we propose to extend the k-means algorithm by introducing pre-aggregates. These aggregates can then be reused to avoid redundant calculations during successive iterations. We show the interest of the approach by several experiments. These last ones show that the more the volume of data is important, the more the pre-aggregations speed up the algorithm.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.229.24.100

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
El malki, N.; Ravat, F. and Teste, O. (2019). k-means Improvement by Dynamic Pre-aggregates.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 133-140. DOI: 10.5220/0007675201330140

@conference{iceis19,
author={Nabil El malki. and Franck Ravat. and Olivier Teste.},
title={k-means Improvement by Dynamic Pre-aggregates},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={133-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007675201330140},
isbn={978-989-758-372-8},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - k-means Improvement by Dynamic Pre-aggregates
SN - 978-989-758-372-8
AU - El malki, N.
AU - Ravat, F.
AU - Teste, O.
PY - 2019
SP - 133
EP - 140
DO - 10.5220/0007675201330140

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.