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澳大利亚斯文伯尔尼科技大学柳诚飞教授讲座通知
点击率:556 作者:中国科大自动化系 来源:http://auto.ustc.edu.cn 时间:2016-07-13 11:06:14

  网络结构化大数据的搜索和查询


报告人:  柳诚飞 教授

报告人单位: 澳大利亚 斯文伯尔尼科技大学 Swinburne University of Technology, Australia

报告时间: 2016714日(周四),上午10:00-11:00

报告地点: 西区电三楼312-314会议室

 

报告摘要:

Big data has become a buzzword. The challenge is how to improve the existing data processing techniques to capture, manage and analyse the data with high volume, variety, velocityand veracity. In this talk, I will introduce several ARC (Australian Research Council) discovery projects we have been conducting in the Web and Data Engineering group at Swinburne University of Technology in Australia. In particular, I will introduce our recent work on keyword search over structured data, community detection over large networks, and advanced query processing and refinement.

 

报告人简介:

Chengfei Liu is a Professor in the Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, Australia. He is the leader of Web and Data Engineering research group and the focus area leader of Knowledge and Data Intensive Systems in the Swinburne University tier-1 Centre for Computing and Engineering Software Systems (SUCCESS). Prior to joining Swinburne, he taught at the University of South Australia and the University of Technology Sydney, and was a Research Scientist at Cooperative Research Centre for Distributed Systems Technology (DSTC), Australia. He also held visiting positions at the Chinese University of Hong Kong, the University of Aizu in Japan, and IBM Silicon Valley Lab in USA. His current research interests include keyword search over structured data, query processing and refinement, XML and RDF databases, graph data management, community discovery, big data management, and workflow management. He was the recipient of the 2007 Vice-Chancellor's Award for Research Excellence at Swinburne. He has served in over 100 organization committees and program committees in international conferences/workshops, and published around 200 peer-reviewed papers in various leading journals and conference proceedings including VLDB J, TKDE, Information Sciences, ICDE, CIKM.

 


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