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Introduction to operations research and data mining

机译：运筹学和数据挖掘概论

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Over the past several years, the field of data mining has seen an explosion of interest from both academia and industry. Data mining is an interdisciplinary field and draws heavily on both statistics and machine learning. In these two areas, such problems as learning how to classify data and finding natural clusters of data have been studied extensively for decades. Furthermore, the earliest mathematical programming formulations of both data classification and data clustering date back almost 40 years. Building on this early work, the recent growing interest in data mining has been paralleled by a similar growth of research in optimization for data mining, and the operations research community has the potential to continue to contribute significantly to this field.
机译：在过去的几年中，学术界和工业界都对数据挖掘领域产生了浓厚的兴趣。数据挖掘是一个跨学科的领域，并且在统计和机器学习上都非常受用。在这两个领域中，诸如学习如何对数据进行分类以及查找数据的自然簇之类的问题已被广泛研究了数十年。此外，关于数据分类和数据聚类的最早的数学编程公式可以追溯到近40年。在这项早期工作的基础上，最近对数据挖掘的兴趣不断增长，与此同时，数据挖掘优化的研究也出现了类似的增长，运筹学界有潜力继续对该领域做出重大贡献。

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