A Reduction Algorithm Meeting Users'' Requirements
A Reduction Algorithm Meeting Users Requirements

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. This work is supported by the National Key Project for Prime Research on Image, Speech, Natural Language Understanding and Knowledge Mining (NKBRSF, Grant No. G 1998030508). ZHAO Kai received his B.S. degree from Beijing Institute of Technology in 1993, and Ph.D. degree from the Institute of Automation, the Chinese Academy of Sciences. His research interests are adaptation systems, genetic programming and data mining. WANG Jue is a professor of computer science and artificial intelligence at the Institute of Automation, the Chinese Academy of Sciences. His research interests include artificial neural network, machine learning and knowledge discovery in database.