Method and device for determining target user

Abstract

The invention discloses a method and device for determining a target user, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: judging a target group to which each item in a preset item set belongs in predetermined item groups; for each target group, obtaining a plurality of primarily selected users of the target group, inputting original feature data of each primarily selected user for each item in the target group into a pre-trained feature generation model, and obtaining optimized feature data of the primarily selected user in the target group; inputting the optimized feature data into a pre-trained user classification model to obtain a classification result of the primarily selected user in the target group; and judging whether the primarily-selected user is a target user corresponding to the article set or not according to the classification result of each primarily-selected user in each target group. According to the embodiment, the target user can be accurately judged based on the predetermined article group.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method and device for determining a target user. Background technique [0002] With the rapid development of Internet technology and new business forms relying on the Internet, service providers need to reach target users more accurately, such as high-potential users with high consumption propensity. At present, service providers generally build target user judgment models based on fixed item category dimensions or brand dimensions. Such models are generally binary classification machine learning models, which mainly construct statistical features based on user behavior information on categories or brands and user attribute information. And take whether the user consumes as the target variable. [0003] In the process of realizing the present invention, the inventors found that there are at least the following problems in the prior art: First, because the fixed item category...

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Problems solved by technology

[0003] In the process of realizing the present invention, the inventors found that there are at least the following problems in the prior art: First, because the fixed item category or brand splits the relationship between items of different categories or different brands, the prior art cannot accurately describe The user's behavior track characteristics for various items, and thus it is impossible to describe their consumption expectations for a specific item pool through user behavior; secondly, the model in the prior art is associated with a fixed item category or brand, so its scope of use is relatively fixed. This is not in line with the dynamic relationship between items based on user behavior; in addition, in the prior art, it takes a lot of manpower and material resources to perform ETL (extract, transform, load) on the original data. Conducive to rapid iteration of business

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