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

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

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 and also 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 by prioritizing the award to them. For further information about this project see the project website at http://arnetminer.org/LDMTA2010