New rough set approach to knowledge reduction in decision table

The core and knowledge reduction of a decision table are the key points of many information process procedures. It has been proved that computing all the reductions and the optimal reduction of a decision table is a NP-complete problem. In this paper, the algorithms for finding relative core and relative knowledge reduction are presented, which are based on the positive region in rough set theory. The effectiveness of the algorithms is demonstrated by some typical examples.