Journal Article10.1109/MIC.2004.1273484
Efficient access to Web services
162
TL;DR: A query optimization model based on aggregating the quality of Web service parameters of different Web services, which adjusts QoWS through a dynamic rating scheme and multilevel matching in which the rating provides an assessment of Web services' behavior.
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Abstract: For Web services to expand across the Internet, users need to be able to efficiently access and share Web services. The authors present a query infrastructure that treats Web services as first-class objects. It evaluates queries through the invocations of different Web service operations. Because efficiency plays a central role in such evaluations, the authors propose a query optimization model based on aggregating the quality of Web service (QoWS) parameters of different Web services. The model adjusts QoWS through a dynamic rating scheme and multilevel matching in which the rating provides an assessment of Web services' behavior. Multilevel matching allows the expansion of the solution space by enabling similar and partial answers.
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Citations
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Toward an agent-based and context-oriented approach for Web services composition
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Personalized Web Service Recommendation via Normal Recovery Collaborative Filtering
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References
Agent-Mediated Electronic Commerce
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G. van Valkenhoef,Sarvapali D. Ramchurn,P. Vytellingum,Nicholas R. Jennings,Rineke Verbrugge +4 more
TL;DR: In this paper, the state of the art of agent-mediated electronic commerce (e-commerce), concentrating particularly on the business-to-consumer (B2C) and businessto-business (b2B) aspects, is surveyed and analyzed.
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Infrastructure for e-government Web services
TL;DR: The core of the research is to develop techniques to efficiently access e-government services while preserving citizens' privacy and designed and implemented an infrastructure called Web Digital Government.
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•Proceedings Article
Are Web Services the Next Revolution in e-Commerce? (Panel)
Data Fusion and Data Quality
Felix Naumann
- 01 Nov 1998
TL;DR: Four techniques of multiple attribute decision making are applied to the problem of quality-driven selection of sources: the Simple Additive Weighting method (SAW), the TOPSIS method, the Analytical Hierarchy Process method (AHP) and the Data Envelopment Analysis method (DEA).
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