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A Survey of Open Source Data Mining Systems

机译:开源数据挖掘系统概述

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摘要

Open source data mining software represents a new trend in data mining research, education and industrial applications, especially in small and medium enterprises (SMEs). With open source software an enterprise can easily initiate a data mining project using the most current technology. Often the software is available at no cost, allowing the enterprise to instead focus on ensuring their staff can freely learn the data mining techniques and methods. Open source ensures that staff can understand exactly how the algorithms work by examining the source codes, if they so desire, and can also fine tune the algorithms to suit the specific purposes of the enterprise. However, diversity, instability, scalability and poor documentation can be major concerns in using open source data mining systems. In this paper, we survey open source data mining systems currently available on the Internet. We compare 12 open source systems against several aspects such as general characteristics, data source accessibility, data mining functionality, and usability. We discuss advantages and disadvantages of these open source data mining systems.
机译:开源数据挖掘软件代表了数据挖掘研究,教育和工业应用中的新趋势,尤其是在中小企业(SME)中。借助开源软件,企业可以使用最新技术轻松启动数据挖掘项目。通常,该软件是免费提供的,从而使企业可以专注于确保其员工可以自由地学习数据挖掘技术和方法。开源确保员工可以通过检查源代码(如果他们愿意)来准确地了解算法的工作原理,还可以对算法进行微调以适合企业的特定目的。但是,多样性,不稳定,可伸缩性和不良文档可能是使用开源数据挖掘系统的主要问题。在本文中,我们调查了Internet上当前可用的开源数据挖掘系统。我们将12个开源系统与几个方面进行了比较,例如一般特性,数据源可访问性,数据挖掘功能和可用性。我们讨论了这些开源数据挖掘系统的优缺点。

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