Aggregation of fuzzy opinions under group decision making
Fuzzy Sets and Systems
A rational consensus model in group decision making using linguistic assessments
Fuzzy Sets and Systems
ACM Computing Surveys (CSUR)
Query clustering using user logs
ACM Transactions on Information Systems (TOIS)
On clusterings: Good, bad and spectral
Journal of the ACM (JACM)
QoS computation and policing in dynamic web service selection
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
QoS Aggregation for Web Service Composition using Workflow Patterns
EDOC '04 Proceedings of the Enterprise Distributed Object Computing Conference, Eighth IEEE International
Composing Web Services: A QoS View
IEEE Internet Computing
Fuzzy Matchmaking for Web Services
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 2
A Moderated Fuzzy Matchmaking forWeb Services
CIT '05 Proceedings of the The Fifth International Conference on Computer and Information Technology
Consumer-centric QoS-aware selection of web services
Journal of Computer and System Sciences
Parallel clustering on the star graph
ICA3PP'05 Proceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing
Fuzzy c-means clustering of incomplete data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A consensus model for multiperson decision making with different preference structures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Survey of clustering algorithms
IEEE Transactions on Neural Networks
Scatter/Gather browsing of web service QoS data
Future Generation Computer Systems
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QoS has been considered as a significant factor for web service marketing and selection. The interpretation of QoS value from web service consumers and providers would be very different. However, a large group of web service participants with different backgrounds may have difficulties in reaching consensus on the values of multi-dimensional web service QoS, so they may have to be clustered in multi-groups in order to improve effectiveness and efficiency. The similarity of clustered fuzzy QoS dispositions as well as their preference order over these attributes should be analyzed to form a multi-groups consensus framework. A soft multi-groups clustering approach could be adopted to prevent opinions from being excluded unintentionally. The group boundaries and similarity thresholds which are used for clustering and analyzing fuzzy QoS opinions can be moderated dynamically according to the feedback from the internal learning mechanism and the web service consumers. As a result, a model for marketing web services based on multi-group consumers' QoS consensus, the FMG-QCMA (Fuzzy Multi-Groups based QoS Consensus Moderation Approach), is proposed to meet the above requirements. The proposed FMG-QCMA is also evaluated through a case study to demonstrate its effectiveness and efficiency in relation to an existing framework, QCMA (QoS Consensus Moderation Approach).