ACollaborative Filtering RecommendationAlgorithm Based on User Preference

Computer & Telecommunication

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Guangzhou City Construction College

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Abstract In this paper, a collaborative filtering recommendation algorithm based on user preference is proposed. First of all, the user similarity is calculated according to the length of the longest common subsequence of different user interest sequences and the num- ber of common subsequences, and then the similarity obtained by this algorithm is weighted and mixed with the similarity obtained by traditional collaborative filtering recommendation algorithm. Project recommendation is completed based on mixed similarity and the possible project score by target users is predicted. Finally, by comparing the average absolute error MAE values of three rec- ommendation algorithms in three data sets of Ciao, Flixster and MovieLens 100K, it is proved that the proposed user collaborative filtering recommendation algorithm (XQCF) has improved the accuracy of the recommendation system.

Key words： collaborative filtering recommendation algorithm user preferences

Published: 24 February 2021

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Cite this article:

SONG Man. ACollaborative Filtering RecommendationAlgorithm Based on User Preference. Computer & Telecommunication, 2020, 1(12): 17-21.

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http://www.computertelecom.com.cn/EN/ OR http://www.computertelecom.com.cn/EN/Y2020/V1/I12/17

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