A Survey on Parallel Method for Rough Set using MapReduce Technique for Data Mining
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 1)Publication Date: 2015-01-05
Authors : Varda C. Dhande; B.V. Pawar;
Page : 423-426
Keywords : Data mining; MapReduce; Rough sets; Approximations; Hadoop; HDFS;
Abstract
In this paper Present survey on Data mining, Data mining using Rough set Theory and Data Mining using parallel method for rough set Approximation with MapReduce Technique. With the development of Information technology data growing at a tremendous rate, so big data mining and knowledge discovery become a new challenge. Rough set theory has been successfully applied in data mining by using MapReduce programming technique. We use the Hadoop MapReduce System as an Implementation platform. The lower and upper approximations are two basic concept of rough set theory. A parallel method is used for the effective computation of approximation and is improving the performance of data mining. With the benefits of MapReduce it makes our approach more ideal for executing large scale data using parallel method.
Other Latest Articles
- Achieving Efficiency of Encrypted Cloud Data with Synonym Based Search and Multi-Keyword Ranked Search
- A Survey on Different Existing Technique for Detection of Black Hole Attack in MANETs
- A Systematic Study for Electrical Properties of Chemically Treated Coir Fiber Reinforced Epoxy Composites with ANN Model
- WBANs for Patient Monitoring Systems: A Survey and Outlook
- eDEW: Effective Data Extraction from Web
Last modified: 2021-06-30 21:20:16