Today we rely on Web Search Engines, like Google or Bing, to find relevant documents among trillions or quadrillions of documents on the Web. The Web also contains a vast amount of structured data in a variety of domains, such as travel, products, bibliographies, finance, and social networks. Current Web search engines and web database query interfaces are insufficient to satisfy the diverse search needs of web users. The information discovery processes are further complicated by the prevalence of uncertain data. At the same time, it is infeasible to request a web user to design clean databases and write precise SQL queries. In this talk, I will discuss the challenges, opportunities, and then some of the solutions that we have developed for empowering web users for effective information search on structured data.
Furthermore, I will discuss how to enable successful social search so that complex computation tasks can be accomplished by leveraging social computing.
Yi Chen is an Associate Professor in Computer Science and an affiliate faculty in Biomedical Informatics at Arizona State University (ASU).
She received her Ph.D. from the University of Pennsylvania and her B.S. from Central South University in 2005 and 1999, respectively. Her research interests include keyword search on structured data, learning uncertain data, workflow management and social computing, with applications in Web, social computing and healthcare. She is a general chair for SIGMOD’2012, a PC chair for KEYS’2009 and DBRank’2012. Yi Chen is a recipient of Outstanding Researcher Award in ASU CSE (2011), a Google Research Award (2011), IBM Faculty Award (2010) and an NSF CAREER Award (2009).