美国加州大学圣塔芭芭拉分校在美国公立大学排名中名列前10，工科专业排名中位列第37,计算机专业排名第18。
讲座题目:Similarity Search and Duplicate Detection for Big Data
讲座时间:2013年4月9日下午3:00-4:30
讲座地点:玉泉校区曹光彪主楼208教室
讲座人: Tao Yang教授
讲座内容简介:
This talk presents performance optimization techniques on scalable similarity search for big data.
It describes the use of all-pair similarity search for duplicate clustering and redundant
content removal in web data management. It also discusses the role of duplicate detection in virtual machine image backup in a large cloud service.
讲座人简历:
Tao Yang received the B.S. degree in Computer Science from Zhejiang University, China, in 1984, the M.E. degree in Artificial Intelligence from Zhejiang University in 1987. He received the M.S. and Ph.D. degrees in Computer Science from Rutgers University in 1990 and 1993. He joined the Department of Computer Science at UCSB in 1993. His research has been in the areas of parallel and distributed systems, web search/mining, and high performance scientific computing with over ninety refereed conference and journal papers. He received the Research Initiation Award from NSF in 1994, UC Regents' Junior Faculty Award in 1994, the Computer Science Faculty Teacher Award in 1995 from the UCSB College of Engineering, and the CAREER Award from NSF in 1997, and Noble Jeeviant Award from AskJeeves, 2002.
He served as Chief Scientist for Ask.com (formally Ask Jeeves) from 2001 to earlier 2010, and also VP/SVP of ASK as the head of its search engineering division in various periods. He was the founding Chief Scientist and Vice President of Research and Development from 2000 to 2001 for Teoma, an Internet search startup company acquired by Ask Jeeves in 2001. At Ask.com/Teoma, he has led teams of scientists and engineers for the design and implementation of a top-rated search engine and vertical products that power Ask.com, Ask Kids , Teoma , and other Ask network sites with over 100 million users. He has co-developed scalable search algorithms and systems for page indexing, retrieval, ranking, classification, and anti-spamming. He has been directly responsible for scaling search architectures for handling billions of documents in terms of relevancy, performance, and freshness. He has visited Microsoft Bing for search technology R&D in 2010 and 2011. Recently, he has also been advising Panguso on search technology.
个人网页: http://www.cs.ucsb.edu/~tyang/
