Rules Generation for Multimedia Data Classifying using Rough Sets Theory

• Main Authors: A. Rahman, M. Nordin, Ahmad Saany, Syarilla Iryani, Yusof, Mohd Kamir, M. Lazim, Yuzarimi
• Format: Article
• Language: English
• Published: 2013
• Subjects: T Technology (General); ZA Information resources
• Online Access: http://eprints.unisza.edu.my/3817/1/FH02-FIK-14-00608.pdf; http://eprints.unisza.edu.my/3817/

An efficient multimedia data management process is very important in multimedia system application. Huge size of multimedia data that distributed in multi locations makes multimedia data management more complicated. Rapid development of multimedia applications created a vast volume of multimedia data and it is exponentially incremented from time to time. This situation requires for efficient data classification and organization technique for providing effective multimedia data manipulation process. Using rough sets theory and web services technology, this paper proposed a new rules generation for multimedia data classifying in collaborative environment. ROSETTA tool is applied to verify the reliability of the generated results. The experiments show that the rough sets theory based for multimedia data classifying is suitable to be executed in web services environment.