Product attribute decision-making method and device based on artificial intelligence and electronic equipment

Abstract

The invention provides a product attribute decision-making method and device based on artificial intelligence, electronic equipment and a computer readable storage medium. The method comprises the steps: calling a purchase probability prediction model based on user data to determine purchase probabilities corresponding to target products when the target products have different candidate attributes, wherein the different candidate attributes are included in a candidate attribute set; determining estimated income based on the candidate attributes and the corresponding purchase probabilities; calling a violation probability prediction model based on the historical use data of the user to determine the violation probability of violation use of the target product by the user, and determining estimated loss based on the violation probability; determining an estimated expectation corresponding to the candidate attribute based on the estimated income and the estimated loss; and taking the candidate attribute with the highest estimated expectation in the candidate attribute set as the attribute of the target product. Through the method and the device, the product attributes can be quickly and accurately determined.

Description

technical field [0001] The present application relates to artificial intelligence technology, and in particular to an artificial intelligence-based product attribute decision-making method, device, electronic equipment, and computer-readable storage medium. Background technique [0002] Artificial intelligence (AI, Artificial Intelligence) involves a wide range of fields and plays an increasingly important value. As a technical subset of artificial intelligence, machine learning models have achieved breakthrough results in many application fields, especially in the financial field, such as determining product attributes based on user data, thereby providing direction for product update iterations. [0003] However, in related technologies, product attributes are only determined based on single-source data. The product attributes determined by this method are often far from actual needs, and appropriate product attributes can only be determined after multiple human adjustment...

AI Technical Summary

Problems solved by technology

[0003] However, in related technologies, product attributes are only determined based on single-source data. The product attributes determined by this method are often far from the actual needs, and it takes many manual adjustments to determine the appropriate product attributes.

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