Built-In Optimization of E-Commerce Site Price Recommendations
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Abstract
Recommender Systems (RSs) are software tools and strategies that suggest items likely to interest a user. We examine the online-store price recommendation system, its design, operations, and methodology. We will also examine the study technique and describe the basic recommendation system functions. Shop cost Recommender Systems (RSs) are software tools and approaches that suggest products to a user. This work aims to design and create an online store price suggestion system using Hybrid methods. The system is based on user ratings or previous purchases. However, this has shown two key issues: challenge of sparsity and scalability the suggested system is created utilising the Object-Oriented Analysis and Design Methodology (OOADM), which is data-driven and focuses on several data views and viewpoints. The system will be an online web application that permits both user and administrative interaction.
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