Authors : B R V Naga Chandra Reddy; Likhith Konakalla; G Prasanth Kumar; K Siva Ganapathi; M Santhosh; M Nageswara Rao

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/2w7fwhp3

Scribd : https://tinyurl.com/bdzf7yk2

DOI : https://doi.org/10.38124/ijisrt/25apr420

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Abstract : E-commerce platforms are essential for businesses to connect with customers and drive sales. However, small businesses often struggle to implement advanced search and recommendation features due to the high costs and complexity of traditional solutions. This project introduces an intelligent and cost-effective system that enhances product discovery and customer engagement through contextual search methodologies. By leveraging semantic understanding, the platform processes user queries effectively, ensuring accurate and relevant search results even for vague or incomplete inputs. In addition to advanced search capabilities, the system integrates a similarity-based recommendation engine, which identifies and suggests related or complementary products. This feature encourages customer exploration, enhances user experience, and boosts sales opportunities. Designed for scalability and computational efficiency, the solution is accessible to small and medium-sized businesses across industries such as electronics, fashion, and groceries. By prioritizing affordability and adaptability, this project provides a practical and impactful e-commerce enhancement, enabling small businesses to compete with larger marketplaces. The system improves customer satisfaction, increases sales, and fosters stronger customer relationships, making it a valuable tool for modern digital commerce.

Keywords : E-Commerce, Contextual Search, Recommendation Engine.

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