Query evaluation management design and prototype implementation

The increasing customer orientation of information technology applications has resulted in a stronger emphasis on providing query evaluation services to the user community. Applications in electronic markets, data warehousing and decision support systems arenas function in highly dynamic environments serving users who demand increasing flexibility in their interactions with the systems. These characteristics limit a direct application of current query evaluation models. We propose the development of a query evaluation subsystem (QUEM) that is equipped with a knowledge base, a learning component and a decision support component to provide greater flexibility to the users and aid in managing system transitions. A prototype termed QUEST has been built and implemented in a quasi-real world setting. The experimental results validate the practical viability of the proposed architecture.