Incomplete information system andits optimal selections

This paper deals with knowledge discovering in incomplete information systems (IIS).By an IIS, we mean a system with unknown data or partly-known data. This kind of system can be regarded as a set-valued system. The selections of an IIS are considered. The relationships between the reducts in the source system and in its selections are investigated. We also present the concept of maximum distribution reducts and optimal selections, from which we provide an approach to acquire decision rules from incomplete decision tables (IDT).