Recommended method, apparatus, apparatus and computer readable storage medium

Abstract

The present application provides a recommendation method, device, equipment, and computer-readable storage medium; the method includes: acquiring trained recommendation models corresponding to multiple marketing scenario types and multiple user data corresponding to multiple user identifiers, so The user data includes user characteristic data and behavior data; the user data are respectively input into each recommendation model to obtain prediction vectors corresponding to each marketing scenario type; a multi-scenario fusion matrix is ​​constructed based on the prediction vectors corresponding to each marketing scenario type, and the multiple The scene fusion matrix includes the prediction probability of a plurality of target user identifiers under each marketing scenario type under each marketing scenario type; determine the target marketing scenario type corresponding to each target user identifier based on the multi-scene fusion matrix; , sending recommendation information corresponding to the target marketing scenario type to the terminal corresponding to each target user identifier. Through this application, accurate recommendation can be realized.

Description

technical field [0001] The present application relates to Internet technology, and in particular to a recommended method, device, equipment and computer-readable storage medium. Background technique [0002] The complete life cycle of a product generally includes five cycles: start-up period, growth period, maturity period, decay period, and exit period. Corresponding to the five life cycles, the intervention activities adopted by the enterprise can be roughly divided into: initial stage - attracting newcomers, growth stage - attracting newcomers, loss warning, mature period - loss warning, loss recovery, paying newcomers, paying active, etc., recession Period—churn recovery, paid active, paid churn recovery, exit period—churn recovery, paid churn recovery, etc. At present, for product life cycle management, enterprises generally use a single scenario for marketing intervention of a single activity. However, many users exist in multiple life cycle stages of a product, ther...

AI Technical Summary

Problems solved by technology

However, many users exist in multiple life cycle stages of a product, therefore, one user will be involved in multiple product life cycle marketing activities, and the current life cycle marketing scheme cannot give users the most prioritized marketing campaigns, not only recommending The accuracy is not high, and it is easy to cause harassment to users

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