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@article{174263,
        author = {K.Seshu},
        title = {ShopSense: An AI-Driven Search,Forecasting,and  Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3314-3317},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174263},
        abstract = {Shopsense simplifies the shopping process for users. It is a web-based application that will extract the prices from various online shopping websites and give the top 5 e-commerce websites offering low prices. It will also be able to predict the price of the product that we are searching for based on the previous price history and it will give a visualization of a chart of future prices and it is also able to recommend the products in various e- commerce websites related to our search results. The system integrates web scraping and APIs to retrieve product data, employs the ResNet-50 model for image-based product classification, and utilizes the ARIMA model for price trend prediction. The proposed framework enhances the shopping experience by offering real- time price comparisons, intelligent forecasting, and personalized recommendations.},
        keywords = {E-commerce, web scraping, price comparison, price prediction, ResNet-50, ARIMA, product recommendation, AI-driven shopping, image-based classification, real-time forecasting.},
        month = {March},
        }