Semantic sparse Web service discovery method based on Gaussian LDA and word embedding

A discovery method and web service technology, applied in the field of semantically sparse web service discovery, can solve problems such as inability to similarity, calculation, etc., and achieve the effects of improving accuracy, good versatility, and wide applicability

Inactive Publication Date: 2017-04-26
SHANDONG UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

This phenomenon of semantic sparseness can lead to the inability to perform effective similarity calculations, which brings new challenges to keyword-based search methods.

Method used

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  • Semantic sparse Web service discovery method based on Gaussian LDA and word embedding
  • Semantic sparse Web service discovery method based on Gaussian LDA and word embedding
  • Semantic sparse Web service discovery method based on Gaussian LDA and word embedding

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Embodiment Construction

[0038] The specific embodiment of the present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

[0039] Such as figure 1 As shown, a semantically sparse Web service discovery method based on Gaussian LDA and word embedding is carried out in the following order:

[0040] Step 1: Collect Web service description documents, preprocess the collected Web service description documents, obtain the characteristic vocabulary in the Web service description documents, and preprocess the vocabulary in the Web service description documents, and obtain a set of prototype words ;

[0041]Step 2: Use the word embedding training model Word2Vec to train the set of prototype words obtained in step 1, and obtain the continuous vector representation of each word in the set of prototype words; use the Gaussian LDA model to train the set of prototype words obtained in step 1 , to get each web service hierarchy;

[0042] Step 3: Use the set...

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Abstract

The invention discloses a semantic sparse Web service discovery method based on Gaussian LDA and word embedding, and specifically relates to the technical field of service computing. The method specifically comprises the following steps in order: collecting a Web service description document, preprocessing the collected Web service description document, obtaining characteristic vocabularies in the Web service description document, preprocessing the vocabularies in the Web service description document, and obtaining a set of a group of prototype words; using a word embedded training model Word2Vec to train the set of the prototype words obtained in step 1, and obtaining a continuous vector representation of each word in the set of the prototype words; using a Gaussian LDA model to train the set of the prototype words obtained in step 1, and acquiring each Web service hierarchical structure; enriching user query by using a set of continuous vectors obtained in step 2 by training, and obtaining extended user query; and using the service hierarchical structure obtained in step 2 and using a probability ranking method to obtain query output corresponding to the extended user query.

Description

technical field [0001] The invention relates to the technical field of service computing, in particular to a semantic sparse Web service discovery method based on Gaussian LDA and word embedding. Background technique [0002] With the change of Internet computing environment and software architecture, Internet-based software service development has become increasingly popular. The highly distributed and autonomous nature of various computing resources in the software service environment brings new challenges to the development of software systems. Service-oriented architecture can deal with such dynamic, changeable and complex problems, so with the development of service-oriented architecture and software-as-a-service technology, service-oriented software development begins to flourish. In this case, the scale of Web services on the Internet began to grow rapidly, as found in the WWW 2008 paper: from October 2006 to October 2007, the number of WSDL services obtained through...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/3344G06F16/3335G06F16/951
Inventor 田刚高艳峰孙承爱
Owner SHANDONG UNIV OF SCI & TECH
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