Abstract:
E-commerce websites have seen significant and quick development in the recent past. There is a vast array of things available, and several websites offer them for sale. This research primarily focuses on the smartphone category, which has a significant influence on the contemporary world. Buyers must quickly check the authenticity and quality of devices. What superior method exists other than seeking input from individuals who have actually purchased and used them? Customer reviews play a significant role in this context. The primary obstacle in this situation is that highly sought-after items, like top-tier cellphones, get an overwhelming number of evaluations, making it impractical for individuals to dedicate the necessary time and patience to read through thousands of them. Therefore, our programme simplifies this work by examining and evaluating all evaluations for each smartphone, enabling the user to determine the experiences of previous consumers while purchasing this device. We use NLP techniques to train a module using pre-rated reviews. Subsequently, we utilize the trained model to assign ratings to user-generated reviews and present them on our web application.
