A Reduction Algorithm Meeting Users' Requirements

摘要

Generally a database encompasses various kinds of knowledge and is shared by many users. Different users may prefer different kinds of knowledge. So it is important for a data mining algorithm to output specific knowledge according to users' current requirements (preference). We call this kind of data mining requirement-oriented knowledge discovery (ROKD). When the rough set theory is used in data mining, the ROKD problem is how to find a reduct and corresponding rules interesting for the user. Since reducts and rules are generated in the same way, this paper only concerns with how to find a particular reduct. The user's requirement is described by an order of attributes, called attribute order, which implies the importance of attributes for the user. In the order, more important attributes are located before less important ones. Then the problem becomes how to find a reduct including those attributes anterior in the attribute order. An approach to dealing with such a problem is proposed. And its completeness for reduct is proved. After that, three kinds of attribute order are developed to describe various user requirements.