Method and device for determining user community information

Abstract

The embodiment of the invention discloses a method and device for determining user community information. According to one specific embodiment, the method comprises the steps: obtaining user information of a preset user set, and constructing a connected graph; extracting connected sub-graphs from the connected graphs through sampling, and extracting user relationship features and community features of the connected sub-graphs; based on the user relationship characteristics and the community characteristics corresponding to the connected sub-graphs, respectively determining user relationship prior information and community prior information corresponding to the connected sub-graphs, and estimating distribution information of communities to which users in the user subsets corresponding to the connected sub-graphs belong by adopting a preset topic model based on the user relationship prior information, the community prior information and the connected sub-graphs; and determining communityaffiliation information of the corresponding users based on the distribution information of the communities to which the users in the user subsets corresponding to the connected subgraphs belong. According to the embodiment, the distribution information of the community to which the user belongs estimated by the topic model is coupled with the community feature and the relationship feature of theuser, so the accuracy of determining the community attribution information of the user is improved.

Description

technical field [0001] Embodiments of the present disclosure relate to the field of computer technology, specifically to the field of machine learning, and in particular to a method and device for determining user community information. Background technique [0002] Communities can be defined by related relationships, such as similar geographical areas or social relationships, or by abstract ideas, such as common hobbies or spiritual emotions. In the Internet field, such as e-commerce or Internet finance, there are often inextricable connections between users, such as users who have a common mobile phone number or bank card number, or users who love to buy the same product or wealth management products. The relationship between this connection and the user's own characteristics can better serve various businesses. Among these features, the user's community tags can identify the nature of the user itself, which can be used for subsequent modeling or other data analysis. [...

AI Technical Summary

Problems solved by technology

Among them, rule matching can only identify individuals based on intuitive standards; supervised classification models are limited by the number of existing labels, have poor generalization, and cannot discover users’ hidden community types; unsupervised models are associated with graphs The model can only extract local information

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