Personalized intelligent detection and recommendation algorithm system based on big data

Article type: Research Article

Authors: Liao, Li

Affiliations: Chongqing City Vocational College, Chongqing, China | E-mail: liaoli@cqcvc.edu.cn

Correspondence: [*] Corresponding author: Chongqing City Vocational College, Chongqing, China. E-mail: liaoli@cqcvc.edu.cn

Abstract: This paper took the course recommendation as an example to prove that the personalized intelligent detection and recommendation algorithm system provides a convenient means for this problem. In view of the problems such as low recommendation accuracy, lack of personalization and long running time of the current personalized course recommendation system, this paper studied the personalized intelligent detection and recommendation algorithm system with the help of big data technology, hoping to solve the existing problems. The general search results of the traditional recommendation system have been unable to meet the needs of users. In order to improve the course recommendation system, this paper used big data technology to build a scientific framework, and made an in-depth analysis of various problems existing in the traditional system and strove to solve them. The results showed that using big data intelligent systems to search for ten sets of intelligent courses had a search accuracy of between 96% and 98%, indicating that big data can achieve more accurate and efficient results in the construction of intelligent course recommendation systems, and can construct a new course recommendation system to meet user needs.

Keywords: Big data technology, intelligent detection and recommendation algorithm system, intelligent course, spark computing framework, customer satisfaction

DOI: 10.3233/IDT-230429

Journal: Intelligent Decision Technologies, vol. 18, no. 1, pp. 257-271, 2024