Research on Video Recommendation Algorithm Based on Bullet Screen
2020
With the rapid development of Internet industry in the era of Web 2.0, the creation and sharing of content becomes more and more easy, and people's access to information changes accordingly. For information consumers, the exponential growth of information reduces the efficiency of information utilization, and users are eager to obtain more valuable information; for information producers, it is also hoped that there is a way to make information be more concerned by potential users. In order to solve this problem, personalized recommendation system is widely used in all aspects. The emergence of video recommendation system enables users to upgrade from active search to automatic recommendation in the way of obtaining videos, which reduces the time for users to find interested videos, makes video browsing more efficient, and greatly improves the user experience of video websites. In this paper, a video recommendation algorithm based on bullet curtain is proposed to improve the existing recommendation algorithm, and improve the relevance of recommendation results with video and users.
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