Research on accuracy analysis and improvement of recommender system based on amazon review

Abstract

Recommender system is a system that uses artificial intelligence and data mining technology to recommend items or services that meet users' preferences based on their historical behaviors and interests. In modern society, people are faced with more and more choices, and the emergence of recommender system can help users filter out valuable content from complex information and improve user satisfaction and experience. In this paper, collaborative filtering is used to implement a recommender system based on Amazon review data set. Meanwhile, Singular Value Decomposition (SVD) and Principal Component Analysis (PCA) are used to conduct dimensionality reduction and other operations on the data. Root Mean Squared Error (RMSE) A value expressed as a recommendation for accuracy. After the establishment of the recommender system and three precision analysis experiments, it achieves this by applying a selected filtering algorithm to the input supplied, which is frequently in the form of user reviews of products.