Big Data Analysis Based on Machine Learning Techniques
Pradeep S1, Jagadish S Kallimani2
1Pradeep S, Research Scholar, Department of Computer Science & Engineering, M S Ramaiah Institute of Technology, Bangalore, India.
2Jagadish S. Kalmani, Department of Computer Science & Engineering, M S Ramaiah Institute of Technology, Bangalore, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 27 September, 2019. | Manuscript published on October 10, 2019. | PP: 4049-4056 | Volume-8 Issue-12, October 2019. | Retrieval Number: L36301081219/2019©BEIESP | DOI: 10.35940/ijitee.L3630.1081219
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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: Most of the online applications such as Amazon, Snap deal, Flip cart and many others, attract customers by presenting user reviews about the services. These services typically include hotels, flights, cabs, holiday plans and many more. The main objective of this paper is to automatically analyze the feedbacks data given by the customers into positive, negative and neutral categories and gives a summarized review in case of multiple sentences is present in the feedback. In this proposed work various sources of data; namely from Flip cart, Snap deal is considered. The method to analyze the data include collecting the data from the mobile/web application sources, filtering the unwanted data, preprocessing and finally analyzing and summarizing the reviews using supervised machine learning techniques.
Keywords: Machine Learning Techniques, Naive Bayesian Semantic Analysis, Support Vector Machines Algorithm, Big Data.
Scope of the Article: Machine Learning