loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Elio Ventocilla and Maria Riveiro

Affiliation: School of Informatics, University of Skövde, Skövde and Sweden

Keyword(s): Growing Neural Gas, Dimensionality Reduction, Multidimensional Data, Visual Analytics, Exploratory Data Analysis.

Related Ontology Subjects/Areas/Topics: Abstract Data Visualization ; Computer Vision, Visualization and Computer Graphics ; General Data Visualization ; Large Data Visualization ; Visual Data Analysis and Knowledge Discovery ; Visual Representation and Interaction

Abstract: This paper argues for the use of a topology learning algorithm, the Growing Neural Gas (GNG), for providing an overview of the structure of large and multidimensional datasets that can be used in exploratory data analysis. We introduce a generic, off-the-shelf library, Visual GNG, developed using the Big Data framework Apache Spark, which provides an incremental visualization of the GNG training process, and enables user-in-the-loop interactions where users can pause, resume or steer the computation by changing optimization parameters. Nine case studies were conducted with domain experts from different areas, each working on unique real-world datasets. The results show that Visual GNG contributes to understanding the distribution of multidimensional data; finding which features are relevant in such distribution; estimating the number of k clusters to be used in traditional clustering algorithms, such as K-means; and finding outliers.

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 44.220.245.254

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:
Ventocilla, E. and Riveiro, M. (2019). Visual Growing Neural Gas for Exploratory Data Analysis. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - IVAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 58-71. DOI: 10.5220/0007364000580071

@conference{ivapp19,
author={Elio Ventocilla. and Maria Riveiro.},
title={Visual Growing Neural Gas for Exploratory Data Analysis},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - IVAPP},
year={2019},
pages={58-71},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007364000580071},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - IVAPP
TI - Visual Growing Neural Gas for Exploratory Data Analysis
SN - 978-989-758-354-4
IS - 2184-4321
AU - Ventocilla, E.
AU - Riveiro, M.
PY - 2019
SP - 58
EP - 71
DO - 10.5220/0007364000580071
PB - SciTePress