【学术报告】Enabling Data Retrieval: By Ranking and Beyond

发布时间:2007-05-29浏览次数:4585

标题:Enabling Data Retrieval: By Ranking and Beyond
报告者:Chengkai Li
时间:5月30日 下午2:30
地点:蒙民伟楼 109室

报告者简介:Chengkai Li is a Ph.D. candidate in the Department of Computer Sci
ence, University of Illinois at Urbana-Champaign. His general research interes
ts are in the field of databases, with current focus on data retrieval. He als
o works on Web information management and XML. Chengkai received a B.S. and a
M.E. in Computer Science from Nanjing University. He is expected to receive Ph
.D. degree from UIUC in October 2007. In Fall 2007, he will join the faculty o
f the University of Texas at Arlington, as an assistant professor in the Depar
tment of Computer Science and Engineering.URL: http://www.ews.uiuc.edu/~cli

讲座内容:Database management systems (DBMSs) are facing challenges in support
ing non-traditional data retrieval for emerging applications. We need retrieva
l systems over data, much like a "Google" for databases, parallel the well-est
ablished information retrieval over text. Such systems should allow users to u
se flexible and intuitive queries capturing their information needs, and to ex
plore the databases effectively. In the talk, I will discuss this exciting res
earch area and introduce my work in this direction. In particular the talk foc
uses on RankSQL, a DBMS that provides a systematic and principled framework fo
r ranking by extending relational algebra. I will further mention our work on
ranking aggregate queries. Effective data retrieval mechanisms go beyond just
ranking. I will discuss our proposal of generalizing Group-By to clustering, p
arallel to the generalization from Order-By to ranking, and combining the two
constructs. Moreover, a brief introduction to our study of inverse ranking que
ries is provided.