Service discovery method combining attention mechanism LSTM and neural topic model

Abstract

The invention discloses a service discovery method combining an attention mechanism LSTM and a neural topic model. The service discovery method comprises the following steps: 1, extracting natural language vocabularies from a label of a Web service description language and preprocessing the natural language vocabularies; 2, conducting semantic enhancement on the keywords extracted in the step 1, and obtaining described topic information through processing by the neural topic model; 3, embedding the keywords in the step 1 by utilizing a pre-trained word vector; 4, on the basis of the step 2 andthe step 3, carrying out described feature extraction by combining bidirectional LSTM of an attention mechanism; and 5, on the basis of the step 4, finding k services with the highest similarity froma registration service library by calculating the similarity of the feature vectors of the query request and the service description. The method has the advantages that semantic information existingin description of Web services is processed and enhanced through external information, and services meeting user function requirements are found in a large number of registration services on the basisof semantics inquired by a user.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a service discovery method combining an attention mechanism-based LSTM and a neural topic model. Background technique [0002] Service-oriented architecture enables a new paradigm of software development and integration, where system functionality is encapsulated as loosely coupled and interoperable services. Therefore, in order to meet the high interoperability and flexibility requirements in the development of modern software applications, more and more web services and cloud services have been developed. The rapid increase in the number of Web services has brought convenience to developers, but at the same time it has brought difficulties to quickly select appropriate services to meet user needs from large-scale service registry. [0003] In existing service registries, most of Web services are described by (WSDL) Web service description language. The number of keywords ex...

AI Technical Summary

Problems solved by technology

[0007] The present invention proposes a service discovery method based on an attention mechanism-based LSTM and a neural topic model, which is used to solve or at least partly solve the technical problem of poor service discovery effect existing in the methods in the prior art

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