Ppt of review and rating
- 1. REVIEW AND RATING NEHA KUMARI SAFALTA KANCHAN RAWAT
- 2. AIM Our motive is to show review and ratings of the products listed on the website on the basis of:- Product as Described Packaging and handling Product Quality Timely delivery Cost only users which are logged in can rate and comment on products which they purchased.
- 3. INTRODUCTION Today E-commerce have become an important part of our day to day life and people are getting dependent on these website products. The user reviews too, are becoming important for customers. Reviews help to reduce this apprehension and re-establish the trust between consumers and merchants that is lacking in the e-Commerce marketplace. Online ratings and reviews give customers a voice, increase consumer confidence, enhance product visibility, and can dramatically increase sales. When it comes down to it, online ratings and reviews provide incredible value and benefits that businesses cannot afford to ignore
- 4. LITERATURE SURVEY To extract and analyse opinions from online reviews, it is unsatisfactory to merely obtain the overall sentiment about a product. In most cases, customers expect to find fine-grained sentiments about an aspect or feature of a product that is reviewed. For example: This phone has a colorful and big screen, but its LCD resolution is very disappointing. We focuses on positive and negative sentiments about each topic of the product that are useful for the customer as well as focuses on how to improve aspect-level opinion mining for online customer reviews.
- 5. PROJECT IDEA The goal is to generate rating for products based on customer reviews Main focus of our project is textual data mining of user comments based on sentiment analysis. We will remove bad words from the comment by comparing each word of comment to the HashMap which contains all the bad words market competitor names etc.
- 6. FLOW DIAGRAM
- 9. RESULT The result of this system will be rating generated by mining user review by applying Naïve Baye’s algorithm. Rating generated will be based on sentiment words in the product review. It will be a numerical value between ‘0-5’ based on the product review contents. This value will be calculated by pre-stored words in database and their respective assigned values.
- 10. LIMITATION Comments with numeric data cannot be considered Languages other than English in comments will not be considered Sarcastic comments will not be considered
- 11. CONCLUSION System developed which will fetch user comments and perform analysis on them Rating is provided to every product making it convenient to customers Rating is given considering every comment making contribution of each comment
- 12. FUTURE SCOPE Benefits for Consumers:- Established more trust in the product and company. Gives consumers a voice. More interaction on the website. Benefits for E-Commerce Businesses Valuable market research Enhances customer service Increase sales
- 13. REFERENCES R. S. Pressman, Software Engineering (3rd Ed.): A Practitioner’s Approach. New York, NY, USA: McGraw-Hill, Inc., 1992. An Opinion Search System For Consumer Products. Qingling Miao,Qiudn Li Sentiment Analysis Of Online Product Reviews With Semi-Supervised Topic Sentiment Mixture Model. Wei Wang Mining Products Features From Online Reviews. Weishu Hu,Zhiguo Gong,Jingzhi Guo