Smart Shopping Assistant

Abstract - The fast growth of online shopping sites has greatly enhanced the convenience of shopping, but it has also made the process of finding the most appropriate product more difficult, because of differences in prices, ratings, reviews, and reliability of sellers in different websites. This paper introduces Smart Shop, a smart web based shopping assistant that will help compare products of several e-commerce sites and suggest the optimal buying choice based on a single assessment methodology. Product information contained in the system includes items such as price, user ratings, review sentiment, number of reviews, durability indicators, reliability of the seller, and availability. Customer reviews are analyzed with the help of Natural Language Processing techniques that retrieve sentiment scores, and a weighted scoring algorithm is implemented to obtain a Smart Score of each product. With this score, products get ranked and the most appropriate one is advised the user. The experimental test in several product lines proves that the proposed system is effective in the combination of quantitative and qualitative parameters to find products of high value. The Smart Shop system saves time in the decision-making process and reduces the effort of the user as well as enhancing the accuracy and reliability of the internet purchases. Keywords - Smart Shopping Assistant, Product Comparison, Recommendation System, Sentiment Analysis, E-Commerce Platforms, Web-Based System, User Reviews, Price Analysis