Artwork recommendation method and device, readable medium and electronic equipment

Abstract

The embodiment of the invention provides an artwork recommendation method and device, a readable medium and electronic equipment, and the method comprises the steps: firstly, the learning of the picture style characteristics of artworks is performed, and then the clustering is performed, thereby enabling the artworks with similar styles to be classified, enabling the dimensionality of the artworksto be reduced, and achieving the purpose of solving the problem of the sparsity of data; Then, the characteristic division Dirichlet process model can screen the preferences of the user groups to obtain style labels which can represent the group interests of the user groups, and then the group interests of the user groups are divided in a finer-grained manner according to the style labels; And finally, performing personalized recommendation according to the obtained style label distribution of each potential group and the probability distribution of the user belonging to each potential group,and generating a recommendation list. According to the technical scheme provided by the embodiment of the invention, the prediction accuracy and recall rate can be effectively improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method, device, readable medium and electronic equipment for recommending artworks. Background technique [0002] With the development of the Internet, there are more and more virtual groups, such as shopping groups, interest groups, and social groups. Group users may have connections and similarities to a certain extent, and obtaining group interest preferences through these similarities and connections is of great significance for personalized recommendations. [0003] The existing recommendation method is to combine the user files in the group into a group file, and generate a recommendation list for a single user in the group according to the group file. However, when actually obtaining the interest preferences of the group, the individual user preferences in the group cannot be simply summed up. Not all artworks collected and / or purchased by users can represent ...

AI Technical Summary

Problems solved by technology

However, when actually obtaining the interest preferences of a group, the individual user preferences in the group cannot be simply summed up. Not all artworks collected and / or purchased by users can represent the interest preferences of the group. In addition, it is necessary to take into account the differences in the distribution of user interests, etc.

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