Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Efficient algorithms for Web services selection with end-to-end QoS constraints
ACM Transactions on the Web (TWEB)
Preference-based selection of highly configurable web services
Proceedings of the 16th international conference on World Wide Web
Adaptive Service Composition in Flexible Processes
IEEE Transactions on Software Engineering
NFP-aware Semantic Web Services Selection
EDOC '07 Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference
Incomplete Preference-driven Web Service Selection
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 1
A quantitative model for user preferences based on qualitative specifications
Proceedings of the 2009 international conference on Pervasive services
On graphical modeling of preference and importance
Journal of Artificial Intelligence Research
Web Service Selection with Incomplete or Inconsistent User Preferences
ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing
Effective and Flexible NFP-Based Ranking of Web Services
ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing
UCP-networks: a directed graphical representation of conditional utilities
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
WCP-Nets: a weighted extension to CP-Nets for web service selection
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
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Most existing approaches of Web service selection with user preferences are either quantitative or qualitative. However, using a qualitative or quantitative approach alone cannot handle all the non-functional properties(NFPs). To solve this problem, we present an approach of service selection with quantitative and qualitative user preferences, where qualitative preferences are modeled as a TCP-net and quantitative preferences are specified by using arbitrary positive numbers. Our approach consists of two steps, that is, qualitative selection based on qualitative preferences and quantitative selection based on quantitative preferences. We prove its effectiveness and verify its efficiency through extensive experiments.