A Peruse on Feature Specific: Quality Prediction of Product using Opinion Mining
K.Sravana kumari1, B.Manjula2
1K.Sravana Kumari , Scholar , Department of Computer Science, Kakatiya University, Warangal, Telangana.
2Dr.B.Manjula, Assistant Professor, Department of Computer Science, Kakatiya University , Warangal, Telangana.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 2349-2354 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5890018520/2020©BEIESP | DOI: 10.35940/ijrte.E5890.018520
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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 field of sentiment analysis, in which the sentiments of the text are collected, analyzed and compiled, has received much attention in recent years. The corresponding growth in this area has led to the emergence of different sub-regions, each of which relates to a different level of analysis or research. This research focuses on the analysis of feelings at his level, with the aim of finding and adding feelings in the entities mentioned in the documents or aspects thereof. An in-depth overview is given of the newest current developments, illustrating the enormous progress that has already been made to find both the purpose that an entity can be as such, or some aspects of it, and the associated sentimentity. Sentiment analysis has received much attention in recent years. In this article, our goal is to address the problem of classifying the polarity of feelings, one of the fundamental problems of sentiment analysis. A general process is proposed to classify the polarity of feelings with a detailed description of the process. The data used in this study are reviews of online products collected through Amazon.com. Experiments are performed both for the classification at the prayer level and for the classification at the revision level with promising results. Finally, we also provide information about our future work in the analysis of sentiments.
Keywords: Opinion Mining, Sentiment Analysis, Sentence Ranking, Product Review.
Scope of the Article: Data Mining.