出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Nowadays rate of growth of data from various applications of resources is increasingexponentially. The collections of different data sets are formulated into Big Data. The data setsare so complex and large in volume. It is very difficult to handle with the existing DatabaseManagement tools. Soft computing is an emerging technique in the field of study ofcomputational intelligence. It includes Fuzzy Logic, Neural Networks, Genetic Algorithm,Machine Learning and Rough Set Theory etc. Rough set theory is a tool which is used to deriveknowledge from imprecise, imperfect and incomplete data. This paper presents an evaluation ofrough set theory applications to data mining techniques. Some of the rough set based systemsdeveloped for data mining such as Generalized Distribution Table and Rough Set System (GDTRS),Rough Sets with Heuristics (RSH), Rough Sets and Boolean Reasoning (RSBR), MapReduce technique and Dynamic Data Mining etc. are analyzed. Models proposed andtechniques employed in the above methods by the researchers are discussed.
关键词：Data Mining; GDT-RS; RSH; RSBR; Map Reduce; Dynamic Data Mining; Rough Set Theory.
