Video recommendation method and system based on Web mining

Abstract

The invention discloses a video recommendation method and system based on Web mining. The method comprises the steps that a data mining algorithm is applied in clicking behavior data when users watch videos through Web mining, a user interest model is built through a classification and regression tree, a traditional collaborative filtering algorithm is adopted to recommend an individualized video to the users, the defect that in a traditional recommendation system, the data sparsity is brought due to the fact that user comment information is little is overcome, the problem of recommendation cold start due to the fact that a new user or a new project has no scores is solved, the satisfaction degree of the users to watch the video is improved, the users having the same interest and hobbies generate a recommendation, and friend recommendation is achieved in the video recommendation system.

Description

technical field [0001] The invention relates to a video recommendation method and system based on Web mining, belonging to the technical field of data mining. Background technique [0002] Now we have entered an era of data explosion. The vigorous development of Web 2.0 makes it easier and easier to create and share content. Internet users publish a large number of pictures, blogs, and videos on the Internet every day. People are gradually changing from lack of information. The era has entered the era of information overload. In this era, both information consumers and information producers have encountered great challenges: for information consumers, the explosive growth of information makes it more and more difficult for people to find the information they need; for information producers , in order to make the information produced by itself stand out and attract the attention of the majority of users, it is also a tricky thing. The recommendation system is an important to...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the data sparsity problem caused by the lack of user comment information in the traditional recommendation system, and alleviate the cold start problem of recommendation for new users or new items without ratings, the present invention proposes a method and method for recommending videos to users based on Web mining. system, this method can actively recommend personalized videos to users, which improves the satisfaction of users watching videos, and the recommendation results are very accurate

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