Subspace Clustering and Visualization of Data Streams

Ibrahim Louhi, Lydia Boudjeloud-Assala, Thomas Tamisier

2017

Abstract

In this paper, we propose a visual subspace clustering approach for data streams, allowing the user to visually track data stream behavior. Instead of detecting elements changes, the approach shows visually the variables impact on the stream evolution, by visualizing the subspace clustering at different levels in real time. First we apply a clustering on the variables set to obtain subspaces, each subspace consists of homogenous variables subset. Then we cluster the elements within each subspace. The visualization helps to show the approach originality and its usefulness in data streams processing.

Paper Citation

in Harvard Style

Louhi I., Boudjeloud-Assala L. and Tamisier T. (2017). Subspace Clustering and Visualization of Data Streams . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017) ISBN 978-989-758-228-8, pages 259-265. DOI: 10.5220/0006169702590265

in Bibtex Style

@conference{ivapp17,
author={Ibrahim Louhi and Lydia Boudjeloud-Assala and Thomas Tamisier},
title={Subspace Clustering and Visualization of Data Streams},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)},
year={2017},
pages={259-265},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006169702590265},
isbn={978-989-758-228-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)
TI - Subspace Clustering and Visualization of Data Streams
SN - 978-989-758-228-8
AU - Louhi I.
AU - Boudjeloud-Assala L.
AU - Tamisier T.
PY - 2017
SP - 259
EP - 265
DO - 10.5220/0006169702590265