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Advances in Data Mining: History and Future

机译:数据挖掘的进展:历史与未来

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摘要

The Data Mining field proposes the development of methods and techniques for assigning useful meanings for data stored in databases. It gathers researches from many study fields like machine learning, pattern recognition, databases, statistics, artificial intelligence, knowledge acquisition for expert systems, data visualization and grids. Data Mining represents a set of specific algorithms of finding useful meanings in stored data. This paper aims to point the most important steps that were made in the data mining field of study in recent years and to show how the overall process of discovering can be improved in the future.
机译:数据挖掘领域提出了为存储在数据库中的数据分配有用含义的方法和技术的发展。它收集了许多研究领域的研究成果,例如机器学习,模式识别,数据库,统计,人工智能,专家系统的知识获取,数据可视化和网格。数据挖掘代表了一组在存储的数据中找到有用含义的特定算法。本文旨在指出近年来在数据挖掘研究领域中最重要的步骤,并说明如何在将来改善发现的整体过程。

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