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首页> 外文会议>Iberian Conference on Information Systems and Technologies >KDD processes in non-relational data: The case of the MineraMongo tool
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KDD processes in non-relational data: The case of the MineraMongo tool

机译：非关系数据中的KDD流程：以MineraMongo工具为例

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摘要

The process of Knowledge Discovery in Databases, or KDD for short, have been intensively used in tasks focused on searching useful information based on data. The reason is that such data is generated in significant volume, high speed and with a large variety, which makes it require accurate, efficient and scalable methods to handle them. Due to this scenario, several tools and methodologies have been developed to enable data analysis and mining processes. However, there is still a lack of KDD methods based on non-relational data. Considering this scenario, this work aims to present a tool capable of providing selection, preprocessing, transformation, mining and data analysis through databases. Our results consist in a case study, which is used to demonstrate the potential of the MineraMongo tool. This research contributes in a framework of analytical and computational techniques.
机译：数据库中的知识发现过程（简称KDD）已广泛用于以数据为基础搜索有用信息的任务中。原因是此类数据的生成量很大，速度很高且种类繁多，这使其需要准确，有效和可扩展的方法来处理它们。由于这种情况，已经开发了几种工具和方法来实现数据分析和挖掘过程。但是，仍然缺少基于非关系数据的KDD方法。考虑到这种情况，这项工作旨在提供一种能够通过数据库提供选择，预处理，转换，挖掘和数据分析的工具。我们的结果包括一个案例研究，该案例研究用于证明MineraMongo工具的潜力。这项研究有助于分析和计算技术的框架。

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