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Web service classification method fusing unstructured information and structured information

A structured information, unstructured technology, applied in the field of Web service classification, can solve problems such as effective identification

Pending Publication Date: 2021-07-13
HUNAN UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Similarly, in the API classification scenario, there are cases where the true category of the API cannot be effectively identified by using unstructured features alone

Method used

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  • Web service classification method fusing unstructured information and structured information
  • Web service classification method fusing unstructured information and structured information
  • Web service classification method fusing unstructured information and structured information

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Experimental program
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Embodiment

[0091] In this embodiment, experiments are performed on the classification method provided by the present invention. The data set, experimental settings, evaluation indicators, comparison methods and experimental results of this embodiment will be described in detail below.

[0092] Dataset and Experimental Setup:

[0093] We conduct experiments with real-world datasets to obtain solid experimental results. The dataset is crawled from the Programmable Web site and released publicly. It can be accessed from the online site. The newly updated dataset includes 12919 WebAPIs and 6206 Mashups. Each API and Mashup has a description document, as well as some tags given by developers or users. And there are 312 categories for mashup services, so the average number of mashups in each category is 6206 / 312 = 19.89, although the number of mashups in each category varies greatly.

[0094] Among all WebAPIs, only 940 WebAPIs are called by Mashups, that is, 7.28% of 940 / 12919= are called...

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Abstract

The invention provides a Web service classification method fusing unstructured and structured information, which comprises the following steps of: firstly, converting each service document into a feature vector by using two document representation methods, namely, topic distribution based on potential Dirichlet allocation (LDA) and a document embedding model Doc2Vec based on a neural network, so as to increase the diversity of classification features; then, by applying a recently proposed network embedding technology Node2Vec, obtaining a structure representation vector from two relation graphs, namely a service calling graph and a service marking graph; and finally, training a classifier through combination embedding connected by the multi-dimensional feature vectors. According to the method, comprehensive experiments are carried out on an actual data set, the effectiveness of the method is proved, and the Web service classification performance can be practically improved.

Description

technical field [0001] The invention mainly relates to the related technical field of Web service classification, in particular to a Web service classification method integrating unstructured and structured information. Background technique [0002] Because of its cross-language, cross-platform, loose coupling and open standards, Web service has become the mainstream implementation technology of SOA (Service Oriented Architecture). With the development of Web2.0 technology, Web services and their components (such as Mashup, etc.) have grown rapidly on the Internet in the past ten years. The increase in the number of Web services has greatly increased the burden on people to efficiently use and manage service repositories. In the past, Web service taxonomy has proven to be an effective technique to alleviate this challenge. As an important tool for exploratory data analysis, Web service taxonomy is essential for us to capture and understand the hierarchical functional struc...

Claims

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Application Information

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IPC IPC(8): G06F16/958G06F16/28G06F16/34G06F16/35G06F40/242G06F40/284G06K9/62G06N3/08
CPCG06F16/958G06F16/35G06F16/285G06F40/284G06F16/345G06F40/242G06N3/088G06F18/2415G06F18/2431
Inventor 康国胜刘建勋肖勇
Owner HUNAN UNIV OF SCI & TECH
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