Video prediction strategy based on Markov modified model

The popularity of newly released video segments has not formed a stable trend, and traditional statistical methods cannot reflect changes in popularity in a timely manner. To solve this problem, this paper proposes a video prediction caching strategy based on the Markov modified model, which can be run when there are not many user historical access records. Simulation experiments show that the realization of dynamic prediction improves the hit rate and response speed, and verifies the effectiveness, accuracy and speed of the algorithm.