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Authors: Pedro Almeida 1 ; Le Gruenwald 2 and Jorge Bernardino 3

Affiliations: 1 ISEC, Portugal ; 2 University of Oklahoma, United States ; 3 University of Coimbra, Portugal

ISBN: 978-989-758-193-9

Keyword(s): Data Mining, Data Mining Tools, Open Source.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Data Management and Quality ; Data Mining ; Data Modeling and Visualization ; Databases and Information Systems Integration ; Datamining ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Information Quality ; Knowledge-Based Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: Businesses are struggling to stay ahead of competition in a globalized economy where there are more and stronger competitors. Managers are constantly looking for advantages that can generate benefits at low costs. One way to have such advantage is using the data about customers, demographic data, purchase history, customer behavior and preferences that can help to take better business decisions. Data Mining addresses the challenges of collecting value inside data and the ways to put that value to use for virtually any area of our lives, including business. In this paper, we address the interest of Data Mining for business and analyze three popular Open Source Data Mining Tools – KNIME, Orange and RapidMiner – considered as a good starting point for enterprises to begin exploring the power of Data Mining and its benefits.

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Paper citation in several formats:
Almeida, P.; Gruenwald, L. and Bernardino, J. (2016). Evaluating Open Source Data Mining Tools for Business.In Proceedings of the 5th International Conference on Data Management Technologies and Applications - Volume 1: DATA, ISBN 978-989-758-193-9, pages 87-94. DOI: 10.5220/0005939900870094

@conference{data16,
author={Pedro Almeida. and Le Gruenwald. and Jorge Bernardino.},
title={Evaluating Open Source Data Mining Tools for Business},
booktitle={Proceedings of the 5th International Conference on Data Management Technologies and Applications - Volume 1: DATA,},
year={2016},
pages={87-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005939900870094},
isbn={978-989-758-193-9},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Data Management Technologies and Applications - Volume 1: DATA,
TI - Evaluating Open Source Data Mining Tools for Business
SN - 978-989-758-193-9
AU - Almeida, P.
AU - Gruenwald, L.
AU - Bernardino, J.
PY - 2016
SP - 87
EP - 94
DO - 10.5220/0005939900870094

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