An Implementation of Big Data Processing to Separate the Payload Based on Classification Tree Model
G. Renukadevi1, K. Selvakumar2, S. Tamilarasan3, S. Venkatakrishnan4
1G. Renukadevi*, Research Scholar, Department of Computer Science & Engineering, Annamalai University, TN, India.
2Dr.K.Selvakumar, Department of Information Technology, Annamalai University, TN, India.
3S.Tamilarasan, Department of Computer Science, Bharathiar University, TN, India.
4Dr. S. Venkatakrishnan, Department of Computer Science, Annamalai University, TN, India
Manuscript received on December 15, 2019. | Revised Manuscript received on December 20, 2019. | Manuscript published on January 10, 2020. | PP: 2357-2359 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8794019320/2020©BEIESP | DOI: 10.35940/ijitee.C8794.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The process of distinguishing different types of data in the SQL server is the challenging task for further processing of big data. The big data is available in the Webpages, social media networks and cloud based web servers. In this implementation, the data can be retrieved from the cloud based web services. The data is temporarily posted in the REST API, and the data stored permanently in the SQL Server. The stored data is processed using the Classification Tree Model. Based on this method, the separation of types of payload is possible. With the help of this implementation, the types of the documents are automatically categorized using the trained data. Previously the training set has to be prepared for distinguishing different payloads and documents.
Keywords: Big data Processing, Classification Tree Model, Separation of Payload, REST API, SQL Server, Machine Learning.
Scope of the Article: Classification