CAREER: Efficient Discovery of Previously Unknown Patterns and Relationships in Massive Time Series Databases

迄今为止，绝大多数关于时间序列数据挖掘的研究都集中在相似性搜索上，而较少关注聚类。然而，从知识发现的角度来看，时间序列数据挖掘中有几个更有趣、更重要、也更具挑战性的重要未解决问题。该项目解决了这些问题。长期目标是创建有效的算法，以允许从大量时间序列数据集中以模式、异常、规律和规则的形式提取知识。由于时间序列数据无处不在，这项工作可能对心脏病学、工业、天文学、医学、生物信息学、金融、气象、娱乐和网络等多个领域都有好处。已经确定了将测试算法的当地工业和科学合作者。为了增强该项目的更广泛影响，将通过扩展 UCR 时间序列数据挖掘档案来传播结果，这将使该项目创建的所有代码、数据集和出版物免费提供给数据挖掘研究人员和从业者。该网站 (http://www.cs.ucr.edu/~eamonn/NSFcareer/NSF.html) 提供了有关该项目的更多信息。该项目的一个特点是让本科生和研究生参与寻找、实施和比较与该项目中开发的方法相关的工作。时间序列数据分析对于商业非常重要，因此该项目将产生超出其科学影响的广泛影响。

To date, the vast majority of research on time series data mining has focused on similarity search and to a lesser extent on clustering. However, from a knowledge discovery viewpoint, there are several important unsolved problems in time series data mining that are more interesting, important, and challenging. This project addresses these problems. The long-term goal is the creation of efficient algorithms to allow the extraction of knowledge in the form of patterns, anomalies, regularities and rules, from massive time series datasets. Because of the ubiquity of times series data, the work may have benefits in areas as diverse as cardiology, industry, astronomy, medicine, bioinformatics, finance, meteorology, entertainment and networking. Local collaborators in industry and science, who will test the algorithms, have been identified. To enhance broader impacts of this project, results will be disseminated by an expansion of the UCR Time Series Data Mining Archive, which will make all code, datasets and publications created by the project freely available to data mining researchers and practitioners. The Web site (http://www.cs.ucr.edu/~eamonn/NSFcareer/NSF.html) provides more information about this project.A special feature of the project is an effort involving undergraduate and graduate students to find, implement and compare relevant work to the approach developed in this project. Time series data analysis is very important for business and thus the project will have broad impact beyond its scientific impact.