Title :
An Evaluation Model for Web Services
Author :
Tao, Han ; He-qing, Guo
Author_Institution :
Dept. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou
Abstract :
The evaluation for Web Services is essential to select Web services from many candidates, but current evaluation models evaluate Web services only by common service attributes, which can not meet the requirements of end users. We propose an evaluation model for Web Services, which customizes reasonable attributes in different domains as evaluation factors, and computes the weights of evaluation factors using a machine learning algorithm. The model is implemented in Web service quality evaluation system (WS-QES), which can provide more accurate, reasonable results to end users
Keywords :
Internet; learning (artificial intelligence); software performance evaluation; Web service quality evaluation system; common service attributes; evaluation model; machine learning algorithm; Availability; Computer science; Context-aware services; Delay; Machine learning algorithms; Web services;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614669
