CSE Profile: Jaideep Srivastava

Jaideep Srivastava
Professor

(612) 625-4012
Office: EE/CS 5-209

Interests

Databases, data mining, multimedia systems

Education

Ph.D. 1988, Electrical Engineering and Computer Science, University of California, Berkeley

M.S. 1985, Computer Science, University of California, Berkeley

B.Tech. 1983, Computer Science, Indian Institute of Technology, Kanpur, India

Research

Web Mining - Application of data mining techniques to Web data: We are investigating how information about content, structure, and usage of the Web can be mined for knowledge useful to various applications. A critical issue is the modeling of human interaction with the Web. We believe that page hits are at too fine a granularity to provide useful information and that user behavior must be analyzed at a coarser granularity. Our approach is to group Web page hits into user transactions, based on clustering, which serve as the units of human interaction with the Web. Our ongoing work uses Markov models to approximate the process a user is going through in browsing the Web. Another interesting issue is to mine for interesting usage patterns in Web logs. Hyperlinks in Web pages capture the author's view of pieces of information linked together, while browsing patterns capture the users' view of it. We consider a usage pattern interesting if there is significant disagreement between the two views. We are using the framework of logic with supports to model the beliefs in this environment, and using information about content, structure, and usage of Web pages to estimate the degrees of these beliefs.

Multimedia System: Multimedia information has had a significant impact on our ability to comprehend the phenomenon producing the information, and this trend continues to accelerate. Providing this information to the user in an effective manner, however, poses a number of significant challenges, including very large data volume, timeliness of data delivery, and overall information quality. Our research approach has been to use (a) the special nature of multimedia information, (b) the nature of infrastructure hardware and software, and (c) the perceptual requirements of end users, to develop a number of mechanisms that can be used in next generation operating systems, networks, and databases for multimedia.