Research on the Representation Methods for Rough Knowledge

Now there exists a lot of information from Internet and the information implies abundant knowledge. But the information is usually uncertain, imprecise, incomplete, coarse, and vague. So it is very difficult to acquire knowledge from the miscellaneous information. One of the effective methods to process this kind of information is Rough Set theory. As an important method of the acquisition and process for knowledge, Rough Set theory has given the algebraic representation for knowledge by means of the equivalence relations of algebra and the inclusion relations of set theory. But this representation makes knowledge understanding difficult. In order to overcome this problem the concept of granulating is proposed and the granular representation for knowledge is suggested. The granular representation for knowledge makes complicated problems simplified. It is nearer to the thinking habits of mankind and it can describe the roughness of knowledge quantitatively. This chapter discusses the algebraic and granular representations for knowledge, respectively. Some definitions, properties, and theorems under two different representations are analyzed. The research results justified that two different representations for knowledge are equivalent, but the granular representation is more direct and easier to be understood.