from    
to    
search  

 


New opportunities for sensing via continuous measurement
Topological and out-of-equilibrium QFTs, and quantum computing
【低维量子物理国家重点实验室杰出学者讲座】Superconductivity and magnetism: tw...
【低维量子物理国家重点实验室杰出学者讲座】Topological and correlated phases i...
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。

今日相关信息
MEMS Research at MAT, TU Berlin
融合 • 交互 • 体验——面向...
 
同类别相关信息
请注意活动取消!清华论坛第60讲:Fut...
清华信息大讲堂第152讲:情感分析与终...
学术交流研讨会:密码学与网络空间安全
Incompatibility between renewable-e...
Big Data Analytics: the New Frontier
学术活动