With online shopping these days, buyers face a challenge to decide which products to buy as they navigate through all the product reviews. These reviews can be overwhelming, biased, and unreliable. Also, the process of going through all the reviews is time consuming and requires a lot of effort. This hinders the buyers from taking effective and efficient decisions to buy a product. The proposed ICDE-BuyAdvisor website presents a novel and user-friendly solution to help the buyers in their decision-making process and save their time and effort by evaluating the products for them using web scraping and machine learning techniques. Once the evaluation of the product reviews is completed, the product will be assigned a score. This will help the buyers to better decide whether they want to buy the product or not.
- Programming Languages: Python3, HTML, CSS, JS
- Web Framework: Flask
- Database: MySQL
- IDE: PyCharm
- VCS: Git and GitHub
- Project Management: JIRA
- Communication: Google Meet