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龙星计划课程-Introduction to Data Mining
龙星计划课程-Introduction to Data Mining
教师介绍
熊辉教授本科毕业于中国科学技术大学,博士毕业于美国明尼苏达大学, 现为美国罗格斯—新泽西州立大学罗格斯商学院管理科学与信息系统系副系主任,副教授并终身教授,担任罗格斯-新泽西州立大学信息安全中心主任。 熊辉博士的主要研究领域包括:数据挖掘、商务智能、移动计算,和信息安全。在一流学术期刊和会议上发表100余篇学术论文。获得2009 罗格斯大学最高学术奖,ICDM-2011最佳研究论文。2009年, 提前两年破格晋升为副教授并终身教授。还应邀连续参与组织国际顶级会议(如KDD, ICDM, ICML, ICDE和SDM),并担任国际会议组织委员会委员/主席(如KDD-2012 Industry and Government Track PC Chair, IEEE International Conference on Data Mining (ICDM) Program Committee Chair,第29届中国数据库学术会议大会主席)。他目前还担任IEEE Transactions on Knowledge and Data Engineering(TKDE)和Knowledge and Information Systems(KAIS)副编辑。另外,熊辉教授还获得多项美国国家科学基金(National Science Foundation, NSF)、国家自然科学基金(NSFC)海外及港澳学者合作研究基金、Citrix Systems Inc.、SAP、AwarePoint、华为、IBM、Panasonic等重要数据挖掘研究项目。

本讲教师:熊辉
所属学科:工科
人  气:31194

课程介绍

Course Description and Objectives:
Recent advances in information technology along with the phenomenal growth of the Internet have resulted in an explosion of data collected, stored, and disseminated by various organizations. Because of its massive size, it is difficult for analysts to sift through the data even though it may contain useful information. Data mining holds great promise to address this problem by providing efficient techniques to uncover useful information hidden in the large data repositories.
Awareness of the importance of data mining for business is becoming wide spread. The industry has created more and more job opportunities for people who have interdisciplinary data analytic skills. Indeed, this course intends to bridge the gap between data mining techniques and business applications. The students have the opportunities to learn both domain and technical knowledge to face the big data challenges in the industry.
The key objectives of this course are two-fold:
(1) to teach the fundamental concepts of data mining and
(2) to provide extensive hands-on experience in applying the concepts to real-world applications.
The core topics to be covered in this course include classification, clustering, association analysis, and anomaly/novelty detection. This course consists of about 13 weeks of lecture, followed by 2 weeks of project presentations by students who will be responsible for developing and/or applying data mining techniques to applications such as intrusion detection, Web usage analysis, financial data analysis, text mining, bioinformatics, systems management, Earth Science, and other scientific and engineering areas. At the end of this course, students are expected to possess the fundamental skills needed to conduct their own research in data mining or to apply data mining techniques to their own research fields.

致谢:本课件的制作和发布均为公益目的,免费提供给公众学习和研究。对于本课件制作传播过程中可能涉及的作品或作品部分内容的著作权人以及相关权利人谨致谢意!
课件总访问人次:27695955
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