Open Source Data Mining Tools Evaluation using OSSpal Methodology

Any Keila Pereira, Ana Paula Sousa, João Ramalho Santos, Jorge Bernardino

Abstract

Data Mining is currently one of the best technological developments that offers efficient ways to analyse massive data sets and get hidden and useful knowledge that can have value to business. The use of Open Source Data Mining tools has the advantage of not increasing acquisition costs for companies and organizations. However, one of the main challenges is to choose the best Open Source Data Mining tool that meet their specific needs. This paper compares three of the top Open Source Data Mining tools: Knime, RapidMiner, and Weka. For the comparison the OSSpal methodology is used, combining quantitative and qualitative evaluation measures to identify the best tool.

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Paper Citation


in Harvard Style

Santos J. and Bernardino J. (2018). Open Source Data Mining Tools Evaluation using OSSpal Methodology.In Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-320-9, pages 672-678. DOI: 10.5220/0006907206720678


in Bibtex Style

@conference{icsoft18,
author={João Ramalho Santos and Jorge Bernardino},
title={Open Source Data Mining Tools Evaluation using OSSpal Methodology},
booktitle={Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2018},
pages={672-678},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006907206720678},
isbn={978-989-758-320-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Open Source Data Mining Tools Evaluation using OSSpal Methodology
SN - 978-989-758-320-9
AU - Santos J.
AU - Bernardino J.
PY - 2018
SP - 672
EP - 678
DO - 10.5220/0006907206720678