Based on equivalence matrix and joint decision matrix

the reason of the existing algorithms inefficiency for rules extraction in massive data set is analyzed.The method of rules extraction and calculating process with serial carry chain based on the arbitrary division are presented.This process about the rules extraction will be changed into many agent (sub-systems) and inter-agent to share data by the "Parallel plus Serial" rule calculation

which can effectively improve the algorithm on the massive data set.Complexity analysis shows that the algorithm is more efficient than those existing algorithms.An example is used to illustrate the efficiency of the new algorithm.At last

experimental result shows that the calculating process with serial carry chain for rules extraction is not only efficient but also scalable.