Popularity forecast of movies based on data mining in content distributed/delivery network
Wang Song · Journal of Computer Applications · 2011
The estimation of the content popularity in the Content Distributed/Delivery Network(CDN) system mainly relies on the experience of administrators,which implies strong subjectivity and cannot guarantee the Quality of Service(QoS).In the paper,the authors firstly preprocessed the data,and obtained the initial knowledge base to predict the film popularity.This paper used data mining techniques to learn the existing knowledge and predict the popularity of films.Thus,the films in the CDN system could be deployed more effectively and efficiently.The movie popularity predicted by Bayesian network classier was compared with the movie popularity predicted by decision tree.On the premise of the same correct classification rate and other classification parameters,the time taken to build model in the Bayesian network classifier can be shorter.Therefore,the Bayesian network classifier was preferred.The method can solve the inaccurate deployment caused by the administrators' subjectivities and improve the efficiency of the CDN system.