Study Of Incremental Updating Algorithm Based On Rough Set Theory And Its Application In Data Mining

Data Mining(MD) is a promising and flourishing frontier in database system and database applications. Data Mining is a multidisciplinary field, drawing from many disciplines. There are lots of methods for Data Mining, and Rough Set methodology is one of important method. This paper study an incremental updating algorithm based on Rough Set Theory. In this paper, Rough Set theory has been discussed, by analyzing and synthesizing Data Mining algorithm based on Rough Set Theory, definition of extended discernibility matrix and extended decision matrix has been introduced, new attribute reduction algorithm and incremental updating algorithm have been presented, namely, attribute reduction algorithm based on extended discernibility matrix and incremental rule acquisition algorithm based on extended decision matrix, incremental updating algorithm of rules has been discussed and researched. Incremental updating algorithm and parallel processing technology are used, which improves the efficiency of Data Mining and deduces the complex of time. The experimental results show that the algorithm is efficient and feasible.