On the Normalized Similarity and Distance Metrics


Similarity and distance metrics are widely used in many research areas and applications. In some applications, similarity or distance metrics normalized with the "size" of the objects being measured are required. In this talk, we will first present a formal definition of similarity metric and then show general solutions to normalize a given similarity or distance metric. Examples and applications of the general solutions will also be presented.


Prof. Kaizhong ZHANG
University of Western Ontario, London, Ontario, Canada

Date & Time

12 Aug 2019 (Monday) 10:30 - 11:30


E11-1006 (University of Macau)

Organized by

Department of Computer and Information Science


K. Zhang received the M.S. degree in mathematics from Peking University, Beijing, China, in 1981, and the M.S. and Ph.D. degrees in computer science from the Courant Institute of Mathematical Sciences, New York University, New York, USA, in 1986 and 1989, respectively.

He is currently a professor in the Department of Computer Science, University of Western Ontario, London, Ontario, Canada. His research interests include bioinformatics, algorithms, image processing and databases.