Abstract. Due to the explosive growth of electronically stored information, automatic methods must be developed to aid users in maintaining and using this abundance of information effectively. In particular, the sheer volume of redundancy present must be dealt with, leaving only the information-rich data to be processed. This paper presents an approach, based on an integrated use of fuzzy-rough sets and Ant Colony Optimization (ACO), to greatly reduce this data redundancy. The work is applied to the problem of webpage categorization, considerably reducing dimensionality with minimal loss of information.
Dimension reduction method based on fuzzy-rough sets and Ant Colony Optimization (ACO) method is proposed REF , which is applied to the web categorisation problem.
Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection
In the Proceedings of the Fifth International Conference on Rough Sets and Current Trends in Computing (RSCTC 2006), LNAI 4259
Engineering Computer Science