Artificial intelligence-based homogeneous api recommendation method and device, electronic equipment and storage medium

By using an AI-based API request volume prediction and scoring model, the problems of automation and timeliness in recommending homogeneous APIs are solved, achieving efficient API resource management and improved user experience.

CN120974203BActive Publication Date: 2026-07-24GUANGDONG ESHORE TECH
View PDF 2 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GUANGDONG ESHORE TECH
Filing Date
2025-08-13
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In existing technologies, the recommendation of homogeneous APIs relies on manual configuration based on the experience of operations and management personnel, which makes it difficult to achieve automation, timeliness, and standardization, and also makes it difficult to cope with large-scale API call requests, resulting in an imbalance in resource allocation.

Method used

By employing an AI-based approach, an API request volume prediction model and an API scoring model are used to automatically obtain the predicted request volume and operational status information of candidate APIs, and dynamically update the scores of candidate APIs, thereby achieving automated and timely API recommendations.

Benefits of technology

It enables automated, timely, and standardized recommendations for homogeneous APIs, improves resource utilization, meets the needs of large-scale API calls, avoids resource allocation imbalances, and enhances user experience.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN120974203B_ABST
    Figure CN120974203B_ABST
Patent Text Reader

Abstract

The application relates to an artificial intelligence-based homogeneous API recommendation method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining a homogeneous API set containing candidate APIs corresponding to a business request according to a business request submitted by a user; obtaining a request quantity prediction value of each candidate API in the homogeneous API set; obtaining running state information of each candidate API in the homogeneous API set; obtaining a basic score of each candidate API in the homogeneous API set, and updating the score of each candidate API based on the request quantity prediction value and the running state information of each candidate API to obtain a latest score result list of each candidate API; and determining a target API matched with the business request recommended to the user according to the latest score result list of each candidate API. The scheme provided by the application can realize timely, automatic and standardized API recommendation, improve the overall resource utilization rate, and meet the demand of AI capability calling of the user.
Need to check novelty before this filing date? Find Prior Art