西安电子科技大学2013年度研究生学术年会
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应用驱动的大规模图数据挖掘

时间:2013-11-29 11:28来源:未知 点击:

报告题目:应用驱动的大规模图数据挖掘

报告时间:2013年11月29日晚19:00

报告地点:北校区图书馆西裙楼三楼报告厅
 
报告摘要::As graph data is ubiquitous and diverse, and can be used to naturally model complex relationships among objects, graph data mining has become an important tool in many applications and has attracted a lot of attention in the database community. Especially, the application-driven graph data mining has shown high utility, while in the meantime it also poses some unique challenges. In recent years we have explored some interesting research problems in this field and I would like to share some research results in this talk. Specifically, some of our recent research on coherent subgraph mining over large dense graph databases, graph generator pattern discovery for classification, graph modeling for personalized recommendation and entity linking, and community detection in large network data will be introduced, and some typical applications of the developed graph mining algorithms will be also illustrated, including stock market data analysis, gene function annotation, image classification, concept disambiguation, ontology population, and personalized recommender systems, and so on.
 
报告人简介:王建勇,清华大学计算机系教授(研究员),博士生指导教师。主要研究方向为数据挖掘及Web数据管理。在国际三大数据挖掘会议(ACM SIGKDDIEEE ICDMSIAM SDM)、国际三大数据库会议(ACM SIGMODVLDBIEEE ICDE)、国际人工智能、万维网及信息检索重要会议IJCAIWWWCIKMWSDM以及国际一流的知识工程/数据挖掘/数据库/数据质量期刊ACM TODSACM TKDDACM JDIQVLDB J.DMKDIEEE TKDE上发表研究论文60多篇。据Google scholar的索引统计,所发表论文已被累计引用超过6000次,单篇最高引用超过1000次。多次担任国际知名会议(如SIGKDDVLDBAAAIICDE)的程序委员会委员(PC)以及SIGKDDICDMSDMCIKM的资深程序委员会委员(Senior PC或程序委员会副主席(Vice PC Chair。目前是IEEE高级会员(senior member)并担任国际知识工程顶级期刊IEEE TKDE的编委(Associate editor)。入选2007年度教育部“新世纪优秀人才”支持计划和2009年度日本大川研究基金资助计划。获得WWW’08的best poster award、 2009年度HP实验室创新研究奖、以及2013年度中国计算机学会自然科学奖二等奖。


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