Finding reductions from decision tables is one of the main objectives in information processing. Many studies focus on attribute reduct that reduces the number of columns in the decision table. The problem of finding all attribute reducts of consistent decision table is exponential in the number of attributes. In this paper, we aim at finding solutions for the problem of decision table reduction in polynomial time. More specifically, we deal with both the object reduct problem and the attribute reduct problem in consistent decision tables. We proved theoretically that our proposed methods for the two problems run in polynomial time. The proposed methods can be combined to significantly reduce the size of a consistent decision table both horizontally and vertically.

Graph mining is a major area of interest within the field of data mining in

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