• Karuna Sahay
• Kaptan Singh
• Amit Saxena

Opinion Mining is the computational detailed investigation of people’s attitudes, opinions, and emotions concerning of issues, events, topics or individuals. The micro-blogging and social network sites are considered as one of the best source of information for the reason that people discuss and freely share their sentiments about a certain subject freely. Posts are generally composed of poorly structured, incomplete, and noisy sentences, irregular expressions, non-dictionary terms, and ill-formed words. The problem is some customers given rating contrast with their comments. The other reviewers must read many comments and comprehend the comments that are different from the rating. Machine learning is about forecasting the future based on the past information. The proposed method provides automatically pre-processing of data and extract words from a sentence using machine learning. The proposed algorithm used improved Support Vector Machine method for better opinion mining and accurate prediction. The proposed method resolved semantic analysis and opinion mining problems to solve different sentiment polarity. The experimental outcome demonstrate that system is well suitable for opinion polarity and prediction.

"Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.115-118, June 2019, Available :http://www.jetir.org/papers/JETIR1906R55.pdf

"Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp115-118, June 2019, Available at : http://www.jetir.org/papers/JETIR1906R55.pdf