An algorithm for case generation from a database Original Research Article

Knowledge acquisition for a case-based reasoning system from domain experts is a bottleneck in the system development process. With the huge amounts of data that have become available, deriving representative cases from available databases rather than from domain experts is highly useful. This paper presents an algorithm based on the similarity-based rough set theory that can derive cases automatically from available databases.