Incremental Core Computing for Incomplete Decision Tables

Core is an important concept of rough set theory and many efficient reduction methods were proposed from the computation of core. However, very little work has been performed on updating a core, especially for incomplete decision tables. In this paper an incremental algorithm for updating the core of an incomplete decision table is presented based on discernibility matrix, which may obtain a new core through several simple operations on original discernibility matrix when a new object is added to the decision table. Theoretical analysis and example show that the incremental core algorithm proposed is efficient for incomplete decision tables.