Abstract: In the incomplete decision information systems, based on similarity relation, the concept of similarity and dissimilarity knowledge is firstly proposed. By the basic knowledge granule, two kinds of rough set model are defined and their properties are discussed. In these rough set models, based on similarity and dissimilarity knowledge, an approach is presented to acquire the positive and negative decision rules, respectively. The certainty factor is introduced to measure their certainty degree. Finally, to simplify these decision rules, this study introduces the heuristic algorithm of the attribute reduction based on the significant attributes and analyzes an illustrative example to prove its effectiveness.