Advancing Knowledge Discovery and Data Mining

Qi Luo
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引用次数: 82

Abstract

Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery and data mining can be extremely beneficial for the field of Artificial Intelligence in many areas, such as industry, commerce, government, education and so on. The relation between Knowledge and Data Mining, and Knowledge Discovery in Database (KDD) process are presented in the paper. Data mining theory, Data mining tasks, Data Mining technology and Data Mining challenges are also proposed. This is an belief abstract for an invited talk at the workshop.
推进知识发现和数据挖掘
知识发现和数据挖掘已经成为越来越重要的领域,因为最近对KDD技术的需求不断增加,包括那些用于机器学习、数据库、统计、知识获取、数据可视化和高性能计算的技术。知识发现和数据挖掘对于人工智能在工业、商业、政府、教育等诸多领域的应用都是非常有益的。本文介绍了知识与数据挖掘的关系,以及数据库中的知识发现过程。提出了数据挖掘理论、数据挖掘任务、数据挖掘技术和数据挖掘面临的挑战。这是一个在研讨会上应邀演讲的信念摘要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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