• SHUBHA.S
• Dr.P.Suresh

Sentiment Analysis also known as Opinion Mining analyses customers opinions, emotions and attitude towards a product/service. With the growing development of internet, lot of product/service review data is generated online by potential customers. In this paper, different Decision Rule Mining techniques are developed to improve customer satisfactory levels based on the review comments which are performed in two steps. Initially the Machine Learning Based Sentiment classification (MLBSC) technique is used to classify the extracted words to a particular class. Opinion words and the class labels are used to obtain regressive factor by adapting various probabilistic rules. This helps to create a final decision to improve customer satisfaction. The opinions and sentiment reviews are evaluated by the customers using probabilistic rules thereby the associative regressive decision rule helps the service providers to improve the customer satisfactory level.

Sentiment Analysis, Opinion Mining, Decision Rule Mining, Regression factor, probabilistic rules.

"Decision Rule Mining Technique to improve customer satisfactory level based on the review comments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.27-36, December-2018, Available :http://www.jetir.org/papers/JETIR1812805.pdf

"Decision Rule Mining Technique to improve customer satisfactory level based on the review comments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp27-36, December-2018, Available at : http://www.jetir.org/papers/JETIR1812805.pdf