Semantic Message Link Based Service Set Mining for Service Composition

Zhao, Anping; Wang, Xiaoyong; Ren, Ke; Qiu, Yuhui

doi:10.1109/skg.2009.21

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…Under the basic architecture of Web services, historical service invocations can be recorded by parsing the corresponding SOAP messages [13]. And in our previous work [14], we use a semantic soap header SSH for gathering necessary semantic interaction information between Web services, which is a collection of management attributes that is padded to every message flowing between Web services. The SOAP message with SSH is shown as Fig.…”

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confidence: 99%

Service Semantic Link Network Discovery Based on Markov Structure

Zhao

Huang

Qiu

2010

2010 Sixth International Conference on Semantics, Knowledge and Grids

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Service Semantic Link Network (S-SLN) is the semantic model for effectively managing Web service resources by dependency relationship among services. In this paper, we provided an effective method for automatic discovering S-SLN based on graphical structure representation of the dependencies embedded in probability model. Markov network is an undirected graph whose links represent probability dependencies. We first learned Markov network structure from Web services data, and then transformed the undirected Markov network structure into directed graph structure of S-SLN based on the joint probability distribution. Finally, experimental results show the effectiveness of the method.

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confidence: 99%

Service Semantic Link Network Discovery Based on Markov Structure

Zhao

Huang

Qiu

2010

2010 Sixth International Conference on Semantics, Knowledge and Grids

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Constructing Service Semantic Link Network Based on the Probabilistic Graphical Model

Zhao¹,

Ma²

2012

IJCIS

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Automatic services collaboration calls for the development of semantically structured service network to maximize the utility of Web services. Service Semantic Link Network (S-SLN) is the semantic model for effectively managing Web service resources by the dependency relationship between services. We provided an effective method for constructing S-SLN based on the graphical structure representation of the dependencies embedded in a probabilistic model. A Markov network is an undirected graph whose links represents probability dependencies. We first learned Markov network structure from Web services data, and then transformed the undirected Markov network structure into a directed graph structure of S-SLN based on the same joint probability distribution. Finally, experimental results show the effectiveness of the method.

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A hypergraph-based service dependency model for cloud services

Wang

Peng

2014

2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI)

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Semantic Message Link Based Service Set Mining for Service Composition

Cited by 4 publications

References 12 publications

Service Semantic Link Network Discovery Based on Markov Structure

Service Semantic Link Network Discovery Based on Markov Structure

Constructing Service Semantic Link Network Based on the Probabilistic Graphical Model

A hypergraph-based service dependency model for cloud services

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