Research on news recommendation algorithm based on user behavior
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Li Chengcheng, Liu Yu, Li Zeng
In order to improve the efficiency and accuracy of the news recommendation. Through the study of user behavior and the analysis of user news browsing behavior log, a news recommendation algorithm based on Markov algorithm is adopted, with collaborative filtering algorithm and user based recommendation algorithm, and the Spark (Computing Framework) is used as the running platform, and the news recommendation algorithm based on user behavior is carried out. Research. Based on the in-depth analysis of parallel algorithm, the Mark off model is established to realize the application in intelligent news recommendation. By comparing the traditional recommendation algorithm, the test results show that the algorithm has obvious improvement in accuracy and execution efficiency, and its function is more intelligent.
Markoff Algorithm, Recommendation Algorithm, Accuracy, News Recommendation