The Second Workshop on Large-Scale Data Mining: Theory and Applications

该项目将提供旅行奖学金，以支持美国学生参加2010年7月25日在华盛顿举行的第二届大规模数据挖掘：理论和应用(LDMTA)研讨会，以及KDD 2010。LDMTA研讨会将涵盖可扩展机器学习和数据挖掘算法及其应用，如医疗信息学、电信、社交网络分析和电子商务等主题。PIS旨在从理论和实验两个角度研究现有机器学习和数据挖掘算法的可扩展性和效率。由于最近许多应用程序中的数据爆炸式增长，政府和公司可以轻松收集数TB、PB或更多的数据。一些传统的数据挖掘算法需要被取代，或者需要彻底重新设计，以通过MapReduceHadoop等并行体系结构来处理这些数据量。研修班的重点正是弥合数据挖掘理论与实践之间的鸿沟，聚焦大规模数据挖掘理论与应用的基础研究。这次研讨会的目的是召集数据挖掘研究和产业界的领军人物，就大规模数据挖掘的需求和挑战发表他们的观点，并吸引研究生学习大规模数据挖掘。拟议的学生支持将吸引美国学生参加这次研讨会，并展示他们关于大规模数据挖掘相关主题的作品，鼓励他们将重点放在大规模数据挖掘这一极具前景的研究方向上作为论文研究。特别是，PIs将努力扩大女性和少数族裔学生的参与，优先将奖项颁发给她们。有关该项目的详细信息，请访问该项目的网站：http://arnetminer.org/LDMTA2010

This project will provide travel fellowships to support US students to attend the 2nd workshop on Large-scale Data Mining: Theory and Applications (LDMTA) in conjunction with KDD 2010 on July 25, 2010 in Washington DC. The LDMTA workshop will cover topics on scalable machine learning and data mining algorithms, and their applications, such as medical informatics, telecommunications, social network analysis, and e-commerce. PIs aim at investigating the scalability and efficiency of existing machine learning and data mining algorithms with respect to both theoretical and experimental perspectives. Due to the recent data explosion in many applications, governments and companies can easily collect data spanning terabytes, petabytes or more. Several traditional data mining algorithms need to be replaced, or drastically re-designed, to handle such volumes through parallel architecture such as MapReduce/Hadoop. The focus of the workshop is exactly to bridge the gap between theory and practice of data mining, focusing on the fundamental research on large-scale data mining theory and applications. The goal of this workshop is to assemble the leaders in data mining research and industry to present their views on the need and challenges for large-scale data mining andalso attract graduate students to study on large-scale data mining.The proposed student support will attract the US students to participate in this workshop and present their works on topics related to large-scale data mining, to encourage them to focus on the extremely promising research direction of large-scale data mining as their thesis research. In particular,PIs will try to broaden the involvement of female and minority students byprioritizing the award to them. For further information about this project see the project website at http://arnetminer.org/LDMTA2010