Dynamic data mining using an electro-optical data warehouse

Large information systems that manage terabytes of data must provide rich functionality so that interesting new applications can be addressed. Since a wealth of data, information and knowledge are resident within these vast repositories, a variety cg knowledge discovery techniques have developed. These techniques are very computationally intensive and require the movement of large amounts of data. In the search for new approaches, optics may be able to help since photons have the very attractive properties of high speed, non-interference, and parallelism. Optical systems can accommodate a large number of parallel, high-bandwidth channels and optical storage devices have very high storage densities. In this research we postulate an electrooptical computer architecture and examine the feasibility of executing a number of alphanumeric and image knowledge discovery algorithms on large multimedia data/knowledge bases with the purpose of increasing performance and functionality.