Design and analysis of an intelligent support system for large databases

Maybe algebra and attribute maybe algebra operations have been studied to handle incomplete information in a relational database system. These operations give the user the opportunity to investigate the set of complete, as well as incomplete, data values which can not be obtained with traditional algebra operations. However, some of these operations may generate data which can be enormous in size, erroneous in semantics, and less informative. An intelligent support system is proposed to remedy some, if not all, of these problems in large databases. The proposed system functions as a filter. It has a strong learning capability which adjusts itself according to the specific characteristics of the underlying database and the requirement of the user´s query. The performance analysis has been carried out through simulation of the proposed system. To provide a test bed for the simulation, an incomplete database has been constructed