Realization of Book Collaborative Filtering Personalized RecommendationSystem Based on Linear Regression Equation

• Autores: Yali Gao, Mohamed F. Yousif
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 831-840
• Idioma: inglés
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• Resumen

  • In the context of information construction, faced with a large number of network information data, inorder to obtain more valuable information in an effective time, researchers put forwardarecommendation algorithm for information explosion. Because the recommendation algorithmhas been successfully applied in many fields such as business, the relevant algorithmsystemhas alsobegun to be fully implemented in the field of books. There are many kinds of recommendationalgorithms, among which collaborative filtering recommendation technology is the most widely used. Therefore, based on the humanized library service concept, this paper mainly studies the influencingfactors of reader satisfaction, and on the basis of constructing multiple linear regression model, clarifies the practical significance of constructing collaborative filtering personalized recommendationsystem for libraries. Then, an improved clustering algorithm is proposed to reduce the dimensionalityof the original matrix, and an empirical analysis is made on the book collaborative filteringpersonalized recommendation system based on linear regression equation by using the operation ideaof calculating the score according to the borrowing time. The final results show that, according tothemultiple linear regression model between reader satisfaction and its influencing factors, in order toimprove library service quality and build a good learning and reading environment, collaborativefiltering algorithm should be combined to build a personalized book recommendation system, andthis system is feasible in practical application..