QoS computation and policing in dynamic web service selection
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
SWSDS: Quick Web Service Discovery and Composition in SEWSIP
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
Web Service Discovery via Semantic Association Ranking and Hyperclique Pattern Discovery
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Investigating web services on the world wide web
Proceedings of the 17th international conference on World Wide Web
QoS-Based service selection and ranking with trust and reputation management
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
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Normally, the web service discovery mechanisms in web-sites have a trade-off between being Quality-driven or transaction cost-driven As goals of our paper, we decide upon several factors including the above-mentioned Quality and Transaction cost factors along with the parameters under each factor and use a priority-based greedy approach to involve minimum number of factors to achieve maximum efficiency in the web service discovery. We also present a model with QoS parameters which in a great way help in rating the web services with the end user's perspective on the basis of three levels of views, namely the business level view, Service level view and System level view. In this paper, we've broadly discussed around twenty eight parameters categorically falling under all the above-mentioned factors. To reduce the complexity of involving all the parameters we follow the mechanism of Greedy approach to evaluate the parameters and estimate the criteria rank for each and every parameter. The core principle of the Greedy approach, in general, is to involve minimum number of input data to achieve the maximum efficiency in the final optimized result.