Abstract: Since the efficiency of traditional rule extraction algorithms based on discernibility matrix in inconsistent decision table is often poor, a quick rule extraction algorithm based on discernibility matrix was proposed to deal with the problem．The definite of simplified decision table is first introduced,and many duplicate objects are deleted in decision table.Then the subsets of discernibility matrix is constructed with respect to different decision classes,which effectively avoids the imbalance of objects and compresses the storage space of algorithm,and adopting the heuristic search strategy with backward greedy to calculate the relative minimal attribute reduction.Some useful decion rules based on reliabi-lity are extracted,what’s more,the reliability is dynamically given,and the algorithm has good adaptability．Finally,example analysis and experiential results show that the proposed algorithm can exact effective decision rules from inconsistent decision table.

Key words: Rough set theory,Inconsistent decision table,Attribute reduction,Rule extraction