Xiaoou Li

Abstract: Vertical partitioning is a design technique widely employed in traditional databases to reduce the number of irrelevant attributes accessed by the queries. Currently, due to the popularity of multimedia applications on the Internet, the need of using partitioning techniques in multimedia databases has arisen in order to use their potential advantages with regard to query optimization. In multimedia databases, the attributes tend to be of very large multimedia objects. Therefore, the reduction in the number of accesses to objects that are not used by the queries (irrelevant) would imply a considerable cost saving in query execution. Nevertheless, the use of vertical partitioning techniques in multimedia databases implies two problems: 1) most vertical partitioning algorithms only take into account alphanumeric data, and 2) the partitioning process is carried out in a static way. In order to address these problems, we propose an active system called DYMOND (DYnamic Multimedia ON line Distribution). It performs a dynamic vertical partitioning in multimedia databases to improve query performance. Experimental results on benchmark multimedia databases clarify the validness of our system.

Biography: Dr. Xiaoou Li obtained B. S degree of applied mathematics in 1991 and PhD degree of Electrical & Electronics Engineering in 1995 from Northeastern University, Shenyang, P. R. China. She had worked in Northeastern University, China for two years after PhD study; then she was a postdoc of National Autonomous University of Mexico (UNAM) from 1998 to 2000. Since April 2000, she has been a professor of Department of Computer Science, The Research and Advanced Studies Centre of the National Polytechnic Institute (CINVESTAV-IPN), Mexico. She was a senior research fellow of School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, UK during the school year 2006-2007; and a visiting professor of School of Engineering, University of California Santa Cruz from January to December in 2010. Currently she is a senior member of IEEE (Institute of Electrical and Electronics Engineers), member of AMC (Academia Mexicana de Ciencias, in English: Mexican Academy of Science), and member of SNI (Sistema Nacional de Investigadores, in English: National Researcher System) level 2. Her research interests include knowledge based system, machine learning and data mining applications, social network analysis, Petri nets, non-linear system identification and control, neural networks, system modeling and simulation, active database system, etc.. She has published more than 100 papers in international journals, book chapters and conferences. She has directed 4 doctoral theses and 15 master theses in CINVESTAV. She has successfully finished two CONACYT (NSF in Mexico) projects in the field of Knowledge and Data Engineering and one collaborative project with University of California Riverside.