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Protein Mechanics: from Single Molecule Force Spectroscopy toProtein-based Bi...
化工系膜中心学术论坛-MOF Chemistry: From design strategies to Applications
清华大学材料科学与工程研究院《材料科学论坛》学术报告:Multi-aspect characteri...
Brain-like spiking neural networks: A 4th generation of neural network models
报告题目:
数据挖掘研究的机遇和挑战
 报告人:
吴信东
美国佛蒙特大学计算机科学系教授、系主任
报告时间:
2006-09-28 10:00
报告地点:
FIT楼1区515
主办单位:
计算机科学与技术系
  简介:

Abstract:
This talk provides an overview on the history, main activities, and most
challenging problems in data mining research. We discuss what are considered
important and worthy topics for future research in data mining.  We hope the
challenging problems (identified with input from some of the most active
researchers in the data mining field) will inspire new research efforts, and
give young researchers (including PhD students) a high-level guideline as to
where the hot problems are located in data mining. The most challenging
problems start with developing a possible unifying theory for data mining.

中文简历:
吴信东,美国佛蒙特大学计算机科学系正教授和系主任。
吴信东教授的研究兴趣涉及数据挖掘(Data Mining)、基于知识的系统(Knowledge-Based Systems)、和万维网信息探索(Web
Information Exploration)。国际顶级学报 <<IEEE Transactions on Knowledge and Data
Engineering >>的主编(2005年1月~2008年12 月),和国际顶级会议ICDM-03、KDD-07的程序委员会主席或协同主席。
吴信东博士是2004年ACM SIGKDD奉献奖得主,以表彰他在创立和推动多种数据挖掘学术活动中所作的贡献。

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