Effective Way to Analyze and Rupture the Assessment using ESB Algorithm
P. J. Beslin Pajila1, C. Karpagavalli2, G. Vijayarani3, T. Mangaiyarkarasi4, R. Madhubalashanmu5
1P. J. Beslin Pajila ,Assistant Professor, Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India.
2Karpagavalli. C, Professor, Department of Computer Science and Engineering, St. Mother Theresa Engineering College, Tuticorin, Tamilnadu, India.
3Vijayarani. G, Assistant Professor, Departmnet of Computer Science and Engineering, SCAD College of Engineering and Technology, Cheranmahadevi, Tirunelveli Dist, TamilNadu, India.
4Mangaiyarkarasi .T, pursuing final year Computer Science and Engineering at Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India.
5Madhu balashanmu . R pursuing final year Computer Science and Engineering at Francis Xavier
Manuscript received on March 16, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 2423-2427 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7991038620/2020©BEIESP | DOI: 10.35940/ijrte.F7991.038620
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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: Study of perception or opinion mining is statistical analysis of the views of the people.In past years, it is one of the most effective fields of research in the language processing and text mining.Our views and interpretations of reality, and the decisions that we make, are largely dependent on how others see and judge the world.A general method for categorizing sentiment polarity is suggested, with detailed descriptions of the process.Data are collected from the students entry such as Feedback mechanism and it is substituted in our research algorithm. Experiments are performed with promising results for both assessment-level categorisation and analysis-level categorization. Finally, we also give insight into our future work on an examination of sentiments.
Keywords: Sentimental Analysis, ESB algorithm, Score, Assessment level.
Scope of the Article: Predictive Analysis.