Decision Making on Customer Review using Sentiment Analysis
Santhosh Kumar K L1, Jharna Majumdar2
1Santhosh Kumar K L, Assistant Professor, Department of CSE, Nitte Meenakshi Institute of Technology, Bengaluru (Karnataka), India.
2Jharna Majumdar, Dean R&D, Professor, Department of CSE, Nitte Meenakshi Institute of Technology, Bengaluru (Karnataka), India.
Manuscript received on 29 April 2019 | Revised Manuscript received on 11 May 2019 | Manuscript Published on 17 May 2019 | PP: 636-639 | Volume-7 Issue-6S4 April 2019 | Retrieval Number: F11300476S419/2019©BEIESP
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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 sentiment analysis is especially required in web based business sites, moreover profitable with person. A consistently expanding measure of results are put away in the web and also the measure of individuals would procuring things from online are expanding. Subsequently, the customers’ opinions are expanding every day. The opinions toward seller provides their inclination. The opinions related to products on the Web, which are useful for both manufacturers and customers. The way toward discovering customer opinion about the item or issue is called as opinion mining. Dissecting the feelings from the separated opinions is characterized as Sentiment Analysis. The objective of opinion mining and Sentiment Analysis is to make system ready to perceive and express feeling about the given context. This work focuses on mining opinions from the sites like flipkart, which enables customer to unreservedly compose the view. It consequently extricates the opinions from the site. It likewise uses algorithms CART, Random Forest and J48 classifier to assign the reviews as negative and positive. At the end we have utilized quality parameters to gauge the level of all algorithms.
Keywords: CART, Random Forest, J48, Sentiment Analysis, Quality Metrics.
Scope of the Article: Software Engineering Decision Support