Evaluating Open Source Data Mining Tools for Business

被引：1

作者：

Almeida, Pedro ^{[1
]}

Gruenwald, Le ^{[2
]}

Bernardino, Jorge ^{[3
]}

机构：

[1] Polytech Coimbra, ISEC, Rua Pedro Nunes, P-3030190 Coimbra, Portugal

[2] Univ Oklahoma, Sch Comp Sci, 110 W Boyd St,Room 150 DEH, Oklahoma City, OK 73019 USA

[3] Univ Coimbra, Ctr Informat & Syst, P-3030290 Coimbra, Portugal

来源：

DATA: PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON DATA MANAGEMENT TECHNOLOGIES AND APPLICATIONS | 2016年

关键词：

Data Mining; Data Mining Tools; Open Source;

D O I：

10.5220/0005939900870094

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：87 / 94

页数：8

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