Digital content resource value evaluation method based on GCA-RFR model

The invention discloses a digital content resource value evaluation method based on grey correlation analysis and a random forest regression GCA-RFR model, and the method comprises the steps: taking avalue chain theory as a main line to explore an influence factor of a content resource value, and constructing a content resource value evaluation index system according to the influence factor; crawling related data of an Internet movie database by means of Python, and cleaning the data by deleting and replacing the data cells to obtain valid data; performing index verification and screening byusing a generalized grey correlation analysis method to obtain a final effective index system; carrying out initial sample screening based on an entropy-Dane grey correlation analysis method, and obtaining a final sample set for model training; and based on the index system and the training data, continuously optimizing a random forest regression RFR model to construct a digital content resource value evaluation method. Ac