报告题目: Seasoning Data Mining and Database Research by Connecting Big Data with Many People
报告时间：2011年7月7日（星期四）上午10点
地点：浙江大学紫金港校区图书信息中心B楼CAD&CG国家重点实验室402室
报告人：裴健 教授
主持人：蔡登 副教授

Abstract:Big data, which refers to the data sets that are too big to be handled using the existing database management tools, are emerging in many important applications, such as Internet search, business informatics, social networks, social media, genomics, and meteorology.  Big data presents a grand challenge for database and data analytics research.  In this talk, I review the exciting activities in my group addressing the big data challenge.  The central theme is to connect big data with people in various ways.  Particularly, I will showcase our recent progress in user preference understanding, context-aware, on-demand data mining using crowd intelligence, summarization and explorative analysis of large data sets, and privacy preserving data sharing and analysis.
Short bio:Jian Pei is currently an Associate Professor and the Associate Director,Research and Industry Relations, at the School of Computing Science, Simon Fraser University.  His research interest is to develop effective and efficient data analysis techniques for novel data intensive applications. Particularly, he is currently working on databases, data mining, web search, information retrieval, and their applications in social networks, healthcare informatics, and business.  His research has been extensively supported by NSERC, NSF, Microsoft, IBM, HP, SAP Business Objects, CIBC, and other industry partners.  He has published prolifically in refereed journals and conferences in his fields.  His publications have attracted more than 10,000 citations according to Google Scholar.  He has served actively in the organization and program committees of many conferences and workshops.  He is the associate-editor-in-chief of IEEE Transactions on Knowledge and Data Engineering, and an associate editor of several premier journals on data mining and knowledge discovery. He is the recipient of several prestigious awards, including an NSERC 2008 Discovery Accelerator Supplements Award, the BC Innovation Council 2005 Young Innovator Award, an IBM Faculty Award, and the KDD 2008 Best Application Paper Award.