学术交流

美国德克萨斯州立大学Byron J. Gao博士访问山东大学信息检索实验室

2013年01月11日

1月8日上午，美国德克萨斯州立大学Byron J. Gao博士应马军教授邀请访问实验室，并为在软件园校区高性能中心第二学术报告厅为软件园校区师生做了一场精彩的学术报告，报告题目是：《The Long Pattern Mining Problem and its Applications》。马军教授主持了报告会。

讲座内容摘要： Data mining is instrumental in today's data-intensive science tackling the challenges of data deluge. Frequent pattern mining is a central topic in data mining. Patterns could be subsets, subsequences or substructures. Frequent patterns are the ones occurring frequently in a dataset. Over the past two decades, frequent pattern mining has drawn unparalleled attention and numerous algorithms have been proposed. Virtually, all such algorithms strive to mine frequent patterns with respect to a minimum frequency threshold, and infrequent ones below the threshold are systematically pruned off for efficiency. But, would those discarded infrequent patterns ever be interesting and useful? In this talk, we discuss the statistical and practical significance of previously ignored long patterns, as well as principled solutions that lead to efficient mining of such patterns from massive data.

讲座人简介：Byron J. Gao received Ph.D. and B.Sc. in Computer Science from Simon Fraser University, Canada, in 2007 and 2003 respectively. He was a postdoctoral fellow at the University of Wisconsin before joining Texas State University in 2008. His research spans several related fields of data mining, databases, and information retrieval. He constantly publishes and serves on reputable international conferences and journals. His research has been supported by the National Science Foundation, Department of Energy, and Texas Higher Education Coordinating Board.