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Recommender System Design Comparison by ezradavidezra is a document available to read on EtoBox.

This paper discusses the design of a preference-based recommender system aimed at improving product suggestions for customers, specifically in the context of e-commerce. It compares two approaches: a traditional collaborative filtering method and a new algorithm that incorporates perceptual similarities based on emotional, sensory, and semantic product characteristics. The study evaluates the performance of the proposed method against the traditional approach, demonstrating that considering perceptual data

Author

ezradavidezra

Language

EN