Personalized Learning Resource Push Evaluation Considering Image Big Data Processing Technology

Abstract

With the continuous development of the social economy, the ways of obtaining learning materials and learning resources have gradually increased, especially the development of the Internet has enabled more high-quality resources to be shared, but it should be noted that it is precisely because of the excessive resources, it is relatively complicated to find suitable and interesting learning resources. In response to these needs and deficiencies, this paper attempts to introduce image big data processing technology, characterizes specific learning characteristics using time decay function by sorting out the business logic of personalized learning resource push, and imports specific learning cognitive levels, and matches with the corresponding learning resources, maximizes the quality service of personalized learning resources, and improves the efficiency of learning resources. The simulation experiment results show that the image big data processing technology is effective and can support the push evaluation of personalized learning resources.