Abstract
To improve the understanding of film and television postproduction for college students in the era of intelligent media, a study is conducted on college students’ short video communication education and audience psychology based on the rapid development of virtual image and the Internet of Things (IoT). Primarily, the collaborative filtering algorithm (CFA) is optimized and combined with the principle of Spark and Hadoop platforms as well as the IoT and virtual image technologies. Then, a hybrid computing model is proposed, and the two algorithms are improved and combined, with 90,000 network video records as data samples. Finally, the push accuracy of the hybrid algorithm and the traditional algorithm is calculated and compared, and based on this, a questionnaire survey on the audience psychology of short video production is carried out for college students. The results show that the time user of the combined algorithm is always at least 0.4 s faster than that of a single algorithm and the running speed of the algorithm with five nodes is nearly 80% higher than the algorithm with a single node. The Spark algorithm with multinode has good versatility in image recording and processing of large groups of college students. When processing more than 100,000 image records, the deviation values of Spark and Hadoop with a single node exceeded 1.1, but the deviation value of the hybrid algorithm was still lower than 1.1. With the increase of data volume, the deviation values of the three algorithms are increasing. Compared with the traditional CFA algorithm, the optimized algorithm has a higher speed in processing data and is more accurate in content pushing. From the questionnaire survey of college students, it is found that contemporary college students are not active in learning knowledge of virtual images. Hence, it is concluded that colleges must carry out relevant courses based on short video communication education and strengthen the short video communication education of college students. A reference is provided for the development of college students’ short video communication education in the digital age.
Reference41 articles.
1. Visual sensor intelligent module based image transmission in industrial manufacturing for monitoring and manipulation problems.;Alhayani;J. Intell. Manuf.,2021
2. A modified similarity measure for improving accuracy of user-based collaborative filtering.;Bakri;Ir. J. Sci,2018
3. Visual imaging method of 3D virtual scene based on VR technology;Bing;Proceedings of the International Conference on Multimedia Technology and Enhanced Learning,2021
4. Welding penetration monitoring for pulsed GTAW using visual sensor based on AAM and random forests.;Chen;J. Manuf. Process.,2021
5. An overview of augmented reality technology.;Chen;J. Phys. Conf. Ser.,2019
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献