Research on Graphic-Text Relationship in Film and Television Works Based on Big Data Model

Abstract

With the rise of microblog, social network, mobile APP, location-based services, and other technologies, the global data has exploded. Big data provides a rich source for data mining and analysis, and the results mined from it will become more meaningful and even full of surprises. In this paper, through the problems in processing film and television data, the corresponding model is established to deal with the corresponding problems. According to the related technologies of big data processing and the filtering algorithm of the model, the processing strategies and methods are put forward. The middle also introduces the big data mining method. Finally, according to the different data characteristics and different data processing requirements of the intelligent analysis system of film and television data, comparing the data of film works and TV dramas, the experimental results show that, based on the big data model, the pictures and words in both film works and TV dramas are inseparable and indispensable. In the later research, we choose the appropriate data processing scheme to design and implement the data processing flow, and successfully apply the film and television big data processing strategy and method proposed in this paper to practice, which provides reliable data support for the content analysis of film and television works. The model-based filtering algorithm calculates the relationship between image and text, turns the point into the probability formula of node-to-meta path, and takes the approximate value to achieve efficient model learning.