Web API association pattern mining method based on graph neural network

A neural network and association pattern technology, applied in the field of WebAPI association pattern mining based on graph neural network, can solve the problem of not being able to dig out the potential relationship of WebAPI, and achieve the effect of accurate effect.

Pending Publication Date: 2022-07-12
XIDIAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above-mentioned deficiencies in the prior art, a method for mining association patterns of Web APIs based on a graph neural network provided by the present invention solves the problem that more potential relationships between Web APIs cannot be mined for user recommendation

Method used

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  • Web API association pattern mining method based on graph neural network
  • Web API association pattern mining method based on graph neural network
  • Web API association pattern mining method based on graph neural network

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Embodiment 1

[0036] like figure 1 As shown, in one embodiment of the present invention, a method for mining association patterns of Web API based on graph neural network includes the following steps:

[0037] S1. Collect the Web API dataset, convert it into a heterogeneous graph, and input the heterogeneous graph into the GraphTransformer Network;

[0038] S2. Based on the heterogeneous graph of the input graph neural network, a multi-channel convolution operation is performed through the graph neural network to obtain several first graph structures;

[0039] S3, splicing and stacking several first graph structures to obtain a second graph structure;

[0040] S4 , inputting the second graph structure into a graph convolutional neural network (GCN) to obtain a classification result, and recommending a user according to the classification result to complete the mining of Web API association patterns.

[0041] In the step S1, the heterogeneous graph includes nodes and edges; the types of no...

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Abstract

The invention discloses a Web API association pattern mining method based on a graph neural network, which comprises the following steps: S1, collecting a Web API data set, converting the Web API data set into a heterogeneous graph, and inputting the heterogeneous graph into the graph neural network; s2, based on the heterogeneous graph input into the graph neural network, performing multi-channel convolution operation through the graph neural network to obtain a plurality of first graph structures; s3, splicing and stacking the plurality of first graph structures to obtain a second graph structure; and S4, inputting the second graph structure into the graph convolutional neural network to obtain a classification result, and recommending to the user according to the classification result to complete mining of the Web API association mode.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a method for mining association patterns of Web APIs based on a graph neural network. Background technique [0002] With the rapid development of the Internet, the relationship between people and computers is getting closer and closer, and the number of network applications is also increasing. For developers, API (application programming interface) calls have become an indispensable way in software development. APIs are usually predefined functions that provide applications and developers with software or hardware-based access to a set of examples program without accessing the source code. With APIs, developers don't have to understand the details of the inner workings of the software. As more and more API services are published on the Internet, how to recommend interesting and reliable APIs to developers to build high-quality and reliable software systems has bec...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/9535G06F16/906G06K9/62G06N3/04G06N3/08
CPCG06F16/2465G06F16/9535G06F16/906G06F16/2462G06N3/08G06N3/047G06N3/045G06F18/2431Y02D10/00
Inventor 徐悦甡张荷李瑞蒋志平黑蕾赵新瑜丁云鹏
Owner XIDIAN UNIV
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