Extracting Environmental Information for Improved Web Service Matching and Identification

Author(s):  
Kalapriya Kannan ◽  
Nanjangud C. Narendra ◽  
Lakshmish Ramaswamy
2013 ◽  
Vol 760-762 ◽  
pp. 1708-1712
Author(s):  
Ying Fang Li ◽  
Ying Jiang Li ◽  
Yan Li ◽  
Yang Bo

At present, as the number of web services resources on the network drastically increased, how to quickly and efficiently find the needed services from publishing services has become a problem to resolve. Aiming at the problems of low efficiency in service discovery of traditional web service, the formal concept analysis ( FCA) is introduced into the semantic Web service matching, and a Matching Algorithm based semantic web service is proposed. With considering the concept of limited inheritance,this method introduces the concept of limited inheritance to the semantic similarity calculation based on the concept lattice. It is significant in enhancing the service function matching in practical applications through adjust the calculation.


Author(s):  
Stefanie Konstantinidis ◽  
Fred Kruse ◽  
Martin Klenke

In Germany, public environmental data are in the responsibility of several different public organisations and institutions. The German Environmental Information Portal PortalU® (www.portalu.de) is a web service operated by the environmental administrations to make digital environmental information easier accessible, usable and exploitable for both citizens and environmental experts. The fruitful long-time co-operation between the environmental administrations is an example for a well working organisational structure within a federal state. In this chapter the PortalU technology and the content of the portal are presented. Due to the current discussion referring to INSPIRE, a special focus is set on publishing INSPIRE conform metadata.


2013 ◽  
Vol 385-386 ◽  
pp. 1679-1683
Author(s):  
Xin Bing Ma ◽  
Xiao Feng Zhou

In this article,take into account QoS characteristics comprehensively and build a reliable QoS ontology model. Based on the model,Web service QoS matching will be divided into three stages.Firstly,make a estimation of semantic comparability between QoS parameters of candidate services meeting the functional requirements and the QoS parameters of requirements in QoSIndependent ontology,find candidate services meeting users needs; Then,according to the critical QoS parameters between adjacent services constraints to further refine the matching between the candidate services;Finally choose the maximum service QoS value meeting the user requests in specific areas. So as to improve the efficiency and accuracy of service matching.


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