DocumentCode
2051199
Title
Service Offer Discovery Using Genetic Algorithms
Author
Zaremba, Maciej ; Vitvar, Tomas ; Bhiri, Sami ; Hauswirth, Manfred
Author_Institution
Digital Enterprise Res. Inst., Nat. Univ. of Ireland, Galway, Ireland
fYear
2011
fDate
14-16 Sept. 2011
Firstpage
23
Lastpage
30
Abstract
Available service descriptions are often specified using abstract definitions of service attributes. However, service consumers are mainly interested in concrete, consumable service offers which are specified using concrete values of service attributes. Service offers, due to their request dependence and dynamicity, have to be generated on-the-fly what may require interaction with a service. We propose a service description model that facilitates creation of consumable service offers. A large number of service offers can be generated considering flexible search requests. In order to address that, we propose a novel approach to dynamic generation of service offers. Our approach is based on genetic algorithms and reduces the number of relevant service offers. For evaluation purposes we apply our approach to the shipping domain where real shipping services on the Web are used to prove the effectiveness and usability of our approach in a real-world domain.
Keywords
Web services; genetic algorithms; consumer service; genetic algorithms; service description model; service offer discovery; Business; Concrete; Educational institutions; Genetic algorithms; Heuristic algorithms; Ontologies; Resource description framework; genetic algorithms; projections of parameters; semantic services; service discovery; service offers;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Services (ECOWS), 2011 Ninth IEEE European Conference on
Conference_Location
Lugano
Print_ISBN
978-1-4577-1532-7
Type
conf
DOI
10.1109/ECOWS.2011.9
Filename
6061098
Link To Document