loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Lydia Boudjeloud-Assala and François Poulet

Affiliation: ESIEA Pôle ECD, France

Keyword(s): Data Mining, interactive genetic algorithm, high dimensional data, data visualization.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Evolutionary Programming ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Usual visualization techniques for multidimensional data sets, such as parallel coordinates and scatter-plot matrices, do not scale well to high numbers of dimensions. A common approach to solve this problem is dimensionality selection. We present new semi-interactive method for dimensionality selection to select pertinent dimension subsets without losing information. Our cooperative approach uses automatic algorithms, interactive algorithms and visualization methods: an evolutionary algorithm is used to obtain optimal dimension subsets which represent the original data set without losing information for unsupervised tasks (clustering or outlier detection) using a new validity criterion. A visualization method is used to present the user interactive evolutionary algorithm results and let him actively participate in evolutionary algorithm search with more efficiency resulting in a faster evolutionary algorithm convergence. We have implemented our approach and applied it to real data s et to confirm it is effective for supporting the user in the exploration of high dimensional data sets and evaluate the visual data representation. (More)

CC BY-NC-ND 4.0

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 18.222.163.31

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:
Boudjeloud-Assala, L. and Poulet, F. (2006). SEMI INTERACTIVE METHOD FOR DATA MINING. In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-42-9; ISSN 2184-4992, SciTePress, pages 3-10. DOI: 10.5220/0002454600030010

@conference{iceis06,
author={Lydia Boudjeloud{-}Assala. and Fran\c{C}ois Poulet.},
title={SEMI INTERACTIVE METHOD FOR DATA MINING},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2006},
pages={3-10},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002454600030010},
isbn={978-972-8865-42-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - SEMI INTERACTIVE METHOD FOR DATA MINING
SN - 978-972-8865-42-9
IS - 2184-4992
AU - Boudjeloud-Assala, L.
AU - Poulet, F.
PY - 2006
SP - 3
EP - 10
DO - 10.5220/0002454600030010
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic