Date of Award
3-2019
Document Type
Project
Degree Name
Master of Science in Computer Science
Department
School of Computer Science and Engineering
First Reader/Committee Chair
Murphy,Owen.
Abstract
With the advent of technology in recent years, people depend more on online reviews to purchase a product. It is hard to determine whether the product is good or bad from hundreds of mixed reviews. Also, it is very time-consuming to read many reviews. So, opinion mining of reviews is necessary.
The main aim of this project is to convert the reviews of a product into a rating and to evaluate the ratings using machine learning algorithms such as Naïve Bayes and Support Vector Machine. In the process of converting the reviews to a rating, score words are created using SentiWordNet and transformed into seven categories from highly positive to highly negative.
Recommended Citation
Chanamolu, Charitha, "REVIEWS TO RATING CONVERSION AND ANALYSIS USING MACHINE LEARNING TECHNIQUES" (2019). Electronic Theses, Projects, and Dissertations. 792.
https://scholarworks.lib.csusb.edu/etd/792