A Data Mining Service for Non-Programmers

Artur Pedroso, Bruno Leonel Lopes, Jaime Correia, Filipe Araujo, Jorge Cardoso, Rui Pedro Paiva

2018

Abstract

With the emergence of Big Data, the scarcity of data scientists to analyse all the data being produced in different domains became evident. To train new data scientists faster, web applications providing data science practices without requiring programming skills can be a great help. However, some available web applications lack in providing good data mining practices, specially for assessment and selection of models. Thus, in this paper we describe a system, currently under development, that will provide the construction of data mining processes enforcing good data mining practices. The system will be available through a web UI and will follow a microservices architecture that is still being designed and tested. Preliminary usability tests, were conducted with two groups of users to evaluate the envisioned concept for the creation of data mining processes. In these tests we observed a general high level of user satisfaction. To assess the performance of the current system design, we have done tests in a public cloud where we observed interesting results that will guide us in new directions.

Paper Citation

in Harvard Style

Pedroso A., Lopes B., Correia J., Araujo F., Cardoso J. and Paiva R. (2018). A Data Mining Service for Non-Programmers. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 1: KDIR; ISBN 978-989-758-330-8, SciTePress, pages 340-346. DOI: 10.5220/0007226003400346

in Bibtex Style

@conference{kdir18,
author={Artur Pedroso and Bruno Leonel Lopes and Jaime Correia and Filipe Araujo and Jorge Cardoso and Rui Pedro Paiva},
title={A Data Mining Service for Non-Programmers},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 1: KDIR},
year={2018},
pages={340-346},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007226003400346},
isbn={978-989-758-330-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 1: KDIR
TI - A Data Mining Service for Non-Programmers
SN - 978-989-758-330-8
AU - Pedroso A.
AU - Lopes B.
AU - Correia J.
AU - Araujo F.
AU - Cardoso J.
AU - Paiva R.
PY - 2018
SP - 340
EP - 346
DO - 10.5220/0007226003400346
PB - SciTePress