Audio-visual recommendation method and system based on information perception

Abstract

The invention provides an audio-visual recommendation method based on information perception and an audio-visual recommendation system based on information perception. The audio-visual recommendation method based on information perception comprises the steps that firstly, user information, movie information and user on-demand record information are preprocessed to form standard input data; obtaining a program global map according to the global film and television data and the user on-demand related data, and amplifying the program global map to form a user-program interaction map; performing learning processing on the user-program interaction diagram to form a movie feature vector and a user feature vector; obtaining short-term interests and long-term interests of the user based on the movie feature vectors and the user feature vectors, obtaining interest vectors of the user based on the short-term interests and the long-term interests, and calculating a normalization probability according to the interest vectors; and sequentially taking a preset number of normalization probabilities from large to small as large probability data, and taking an item corresponding to the large probability data as an audiovisual recommendation list, so that fusion of various heterogeneous information is realized.

Description

technical field [0001] The present invention relates to the technical field of media recommendation, and more specifically, to an audio-visual recommendation method and system based on information perception. Background technique [0002] With the advent of the Internet age, the content information on various websites has exploded. Users are often unable to extract effective information of interest or choose suitable products from massive amounts of information. The emergence of personalized recommendation systems provides users with a more efficient decision-making environment. Great progress has been made in various areas of recommendation algorithm research, such as content-based recommendation algorithms, collaborative filtering-based recommendation algorithms, and hybrid recommendation algorithms. These recommendation algorithms tend to use all historical interaction data to obtain users' long-term and static preferences for items. However, in the field of movie busin...

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Problems solved by technology

[0004] In view of the above problems, the purpose of the present invention is to provide an audio-visual recommendation method based on information perception to solve the problem that most of the recommendation methods in the prior art can only obtain the user's long-term and static preferences for items, and cannot capture the user's dynamic preferences. And most of the existing methods only rely on single-layer session data, lack of auxiliary information from other layers, and are prone to cold start and data sparse problems

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