Constructing Service Semantic Link Network Based on the Probabilistic Graphical Model

DOI

10.1080/18756891.2012.747660How to use a DOI?

Keywords

Web service, Probabilistic graphical model, S-SLN, Service relationship

Abstract

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Anping Zhao
AU  - Yan Ma
PY  - 2012
DA  - 2012/11/01
TI  - Constructing Service Semantic Link Network Based on the Probabilistic Graphical Model
JO  - International Journal of Computational Intelligence Systems
SP  - 1040
EP  - 1051
VL  - 5
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.747660
DO  - 10.1080/18756891.2012.747660
ID  - Zhao2012
ER  -