An Overview of a Tool for Extracting Rules from Databases with Incomplete Information

Abstract

The problem of knowledge discovering in the form of rules from databases with incomplete information is studied. At first, the rule extraction from databases without incompleteness is surveyed according to the rough sets theory. Then, databases with incomplete information and the ride extraction from these databases are outlined. We briefly survey our previous research, and apply it for realizing some programs of the rule extraction. The implemented programs and the real execution of these programs are shown, too. In this way, a tool for extracting rides from databases with incomplete information is proposed.