Article Details

Abstract

In today's era of information explosion, users face a huge number of choices when selecting film and television works. Aiming at the shortcomings of the current film and television recommendation system in recommendation accuracy, management efficiency and scalability, this paper proposes a solution based on the Spark framework. This paper adopts the Spring Boot and Vue frameworks for front-end and back-end separation development, uses the Spark application program developed by Scala and combines with the Content-Based Recommendation to process and analyze the user behavior data. The experimental results show that the system performs well in large-scale data processing, significantly improves recommendation accuracy and user satisfaction, and has good scalability, which improves the operating efficiency and user experience of the system as a whole.

Keywords

Spark; Spring Boot; Vue; Scala; film and television recommendation based on content

References

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Funding

Philosophy and Social Sciences Research Project of Jiangsu Province Universities in 2024 (2024SJSZ0253); Research Project on Education and Teaching Reform at the School Level of Zijin College, Nanjing University of Science and Technology (2024010303); Nanjing University of Science and Technology Zijin College Campus level Scientific Research Project (2023ZRKX0401010)

About the authors

Zhang Zhigang (1978-), male, Han nationality, from Changshu, Jiangsu, engineer, master's degree, research direction: embedded systems, testing methodology; Corresponding author: You Fengqin (1983-), female, Han ethnicity, from Jiangyan, Jiangsu, senior engineer, CCF member (U5798M), master's degree, research direction: embedded systems, algorithm design and optimization; Xie Yekang (2000-), male, Han ethnicity, from Lishui, Zhejiang, undergraduate studies, research direction: big data technology and applications; Li Jian (2002-), male, Han ethnicity, from Nanyang, Henan Province, is currently pursuing a bachelor's degree with a research focus on computer application technology.