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Knowledge Discovery-Databases

The rate at which data are stored is growing at a phenomenal rate. Much of the data are imprecise. Knowledge discovery seeks to discover noteworthy, unrecognized associations between data items in the existing database. Topics in this course include: (i) non-trivial extraction of implicit, previously unknown, and potentially useful information from extensional data; (ii) combining extensional data and intentional information for increasing the quality of the knowledge extracted; (iii) systems of reasoning under uncertainty using rough sets (eg Rosetta, RSES, RSGUI); (iv) rough/fuzzy hybrid systems; (v) query processing and data manipulation using rough set based Infobright knowledge grid to achieve data compression. PREREQ: consent of the instructor. (lec 3) cr 3.

Mathematics & Computer Science