Application of Distributed Hybrid Recommendation Algorithm in News Communication

The hybrid recommendation algorithm is a combination of two algorithms, one for each task. The purpose of this paper is to propose a hybrid algorithm that combines the best features of the two algorithms. This paper mainly studies news communication and how to use hybrid recommendation algorithm to improve news communication. The first algorithm used in the hybrid system is collaborative filtering, which uses information about user preferences to recommend news items to users based on user preferences. The second algorithm used in the system is content-based recommendation, which uses text or video data from news articles and videos. In order to better meet the personalized needs of the people at the grass-roots level, the news industry has put forward a distributed hybrid recommendation algorithm for news communication according to the efficiency and other problems existing in the actual development. This form not only breaks through the application mode of the traditional hierarchical clustering algorithm, but also integrates multiple communication features for interest analysis, which helps to provide users with interesting news information faster. On the basis of understanding the current situation of news communication and technology application, this paper analyzes the content of distributed hybrid recommendation algorithm based on news communication, and defines how to effectively implement it according to practical cases, in order to provide an effective basis for the innovation and development of the news industry. This article analyzes the content of distributed hybrid recommendation algorithms based on news communication based on an understanding of the current situation of news communication and technology applications, and clarifies how to effectively implement them based on practical cases, with a view to providing an effective basis for the innovation and development of the news industry.