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A Novel Open Service Framework Mining (OSFM) For Executing Data Mining tasks

Author(s): Mr. Asif Ali | Prof. Gajendra Chandel

Journal: International Journal of Advanced Computer Research
ISSN 2249-7277

Volume: 1;
Issue: 1;
Start page: 28;
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Keywords: Data Mining | OFSM | Prune | Open Framework

Data mining services on grids is the need of today’s era. Workflow environments are widely used in data mining systems to manage data and execution flows associated to complex applications. Weka, one of the most used open-source data mining systems, includes the Knowledge-Flow environment which provides a drag-and-drop inter-face to compose and execute data mining workflows. It allows users to execute a whole workflow only on a single compute on the basis of simplicity. There are several workflows in today’s scene. Most data mining workflows include several independent branches that could be run in parallel on a set of distributed machines to reduce the overall execution time. In this paper we proposed a novel Open Service Framework Mining (OSFM) for executing data mining tasks. Our algorithm contains five phases 1) Authentication 2) Reading Database3) Define the minimum support 4) Subset Find 5) Prune phase. Finally our algorithm shows better performance showing the simulation result.
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