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Cited by 217 publications
(12 citation statements)
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“…Seq (·) is an operator of sequence. If a composite service that performs either the service 1 followed by the service 2 , or 2 followed by 1 S , it is called unordered sequence. In practice, we can decide the order by any condition since the order is not important, then unordered sequence could be treated as sequence.…”
Section: Composite Constructsmentioning
confidence: 99%
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“…Seq (·) is an operator of sequence. If a composite service that performs either the service 1 followed by the service 2 , or 2 followed by 1 S , it is called unordered sequence. In practice, we can decide the order by any condition since the order is not important, then unordered sequence could be treated as sequence.…”
Section: Composite Constructsmentioning
confidence: 99%
“…To establish the existence of a global component market in order to enforce extensive software reuse, service composition has received increasing research efforts. Current technologies based on universal description, discovery, and integration (UDDI), web service description language(WSDL),and simple object access protocol (SOAP) do not realize complex web service combinations, hence providing limited support in service composition [1,2].Web services should be based on open standards, platform independent, application independent, and enable to share data and resources. Web service composition is a task of combining and linking existing web services to create new web processes in order to add value to the collection of services.…”
Section: Introductionmentioning
confidence: 99%
“…The web services [1,2] in the QWS dataset are classified into four categories, such as: 1) Platinum (high quality); 2) gold; 3) silver and 4) bronze (low quality). The classification is measured based on the overall quality rating provided by WSRF.…”
Section: Description Of Qws Datasetmentioning
confidence: 99%
“…When the variable C is observed in the training data, naive Bayes can be used for classification, by assigning test example (X 1 , ···, X n ) to the class C with highest P(C|X 1 , ···, X n ) [2]. When C is unobserved, data points (X 1 , ···, X n ) can be clustered by applying the EM algorithm with C as the missing information, each value of C corresponds to a different cluster, and P(C|X 1 , ···, X n ) is the point's probability of membership in cluster C [14].…”
Section: Naïve Bayesmentioning
confidence: 99%
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