• R.Sangeetha
• K. Logesh

The Main aim of this project is finding the opinion of the product on the marketing based on their reviews. Online reviews can help them improve the quality of services and products. However, it is a challenging issue to acquire the valuable online reviews by recognizing the review sentiment. This project will dynamically identify the customer opinion about the particular product whether the customer will have a positive or a negative opinion about the product. Online reviews have become an important source of information for users before making an informed purchase decision. Identifying reviews is helpful to monitor and manage early promotion and also reviewers are likely to be actual adopters of a product, leading to direct purchase. The final report is generated based on the positive and negative opinion of the customers.

Aspect category detection, consumer reviews, co-occurrence data, sentiment analysis, spreading activation.

"DETECTING ASPECT CATEGORIES FOR ONLINE REVIEW SUMMARIZATION USING SUPERVISED AND UNSUPERVISED METHODS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.187-193, June 2019, Available :http://www.jetir.org/papers/JETIR1906L27.pdf

"DETECTING ASPECT CATEGORIES FOR ONLINE REVIEW SUMMARIZATION USING SUPERVISED AND UNSUPERVISED METHODS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp187-193, June 2019, Available at : http://www.jetir.org/papers/JETIR1906L27.pdf