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In the current landscape, product prices exhibit significant variations across diverse ecommerce platforms.Numerous price comparison websites have emerged to aid users in finding their desired products at the best prices.However, these systems face challenges such as irrelevant search results, outdated product prices, and accuracy issues.This study seeks to address these challenges by developing a user-friendly system.Our system comprises two components.JSoup is employed for data collection, while TF-IDF, SVD, and Cosine Similarity are integrated for product offerings.The proposed platform gathers data from reputable retailers, analyzes it to extract product information, and presents the findings to consumers.We evaluated the system's performance using real data obtained from various marketplaces.The results demonstrate that our system achieved an acceptable accuracy rate when compared to similar industrial solutions and relevant literature.Consequently, users are empowered to make more informed purchasing decisions, leveraging the capabilities provided by the proposed system.
Özakyıldız et al. (Tue,) studied this question.