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An Ensemble based Machine Learning Approach for Analyzing the Sentiments of Scientific

Sitaram Patel, Nikhat Raza khan


The study of Sentiment analysis (SA) and opinion mining (OM) is a field which has developed significantly in the past 10 years. The main intend of this scientific analysis is to decide objectively perspective of the critic and also to equate this with evaluation of the author. This district of study attempt to conclude approach, opinions as well as emotions of people on something or somebody else. This would enable scientists to identify, analyze and analytical evaluation of a scientific report across the board. The interpretation of review is provided by an ensemble method that combines the machine learning (ML) algos with the processing of natural languages. This approach uses part-of-speech (POS) to get syntactic sentence structure. A variety of experiments have been performed to evaluate strengths and efficiency of proposed approach virtual to measurements, utilizing standard metrics, like consistency, precision, recall & F1. This syntactic structure or vocabulary usage will help us assess semantic direction of the analysis by means of an algo. The findings reveal that developments in the binary, ternary or 5-point classification of classic ML algos like bagging and boosting are also difficult to enhance the classification of multi classification in this area.

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