Tutorial Workshop on Mathematical Techniques to Mine Massive Data Sets; July 12-15, 1997; Chicago, Illinois

小行星9714104 该奖项支持为期四天的题为“挖掘海量数据集的数学技术”的研讨会。 研讨会的目标是向一组数学科学家介绍用于挖掘大量数据集的技术。 数据挖掘是在大型数据集中自动提取和发现模式、关联、变化、异常和重要结构。 由科学、工程、医疗和商业应用程序生成的大型数据集正变得越来越普遍。 开发能够在大数据集中发现模式的算法是一个重要的数学挑战。 在过去的十年中，从包括科学、医疗、通信和制造业在内的各个领域以惊人的速度生成了大量数据。 这些数据库的增长速度比计算机的速度快得多，因此超过了我们用现有技术提取信息的能力。 本次研讨会的目的是让数学科学家熟悉大量数据集的挖掘所涉及的问题，并利用他们的抽象能力来获得解决这一关键问题的新方法。

9714104 Grossman This award supports a four-day workshop entitled "Mathematical Techniques to Mine Massive Data Sets". The goal of the workshop is to introduce a group of mathematical scientists to techniques used for the mining of massive data sets. Data mining is the automatic extraction and discovery of patterns, associations, changes, anomalies, and significant structures in large data sets. Large data sets generated by scientific, engineering, medical and business applications are becoming increasingly common. Developing algorithms which can uncover patterns in large data sets is an important mathematical challenge. In the past decade, extremely large sets of data have been generated at an alarming from very diverse areas including scientific, medical, communications, and manufacturing. These data bases are growing much faster than the speed of computers and thus are outstripping our ability to extract information with current techniques. The aim of this workshop is to acquaint mathematical scientists with the issues involved in the mining of massive data sets and to use their ability of abstraction to obtain new approaches to this critical problem.