Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Agglomerative clustering of symbolic objects using the concepts of both similarity and dissimilarity
Pattern Recognition Letters
A model for web services discovery with QoS
ACM SIGecom Exchanges
Clustering of interval data based on city-block distances
Pattern Recognition Letters
QoS computation and policing in dynamic web service selection
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
QoS in Ontology-Based Service Classification and Discovery
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
New clustering methods for interval data
Computational Statistics
Preference-based selection of highly configurable web services
Proceedings of the 16th international conference on World Wide Web
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Symbolic Data Analysis and the SODAS Software
Symbolic Data Analysis and the SODAS Software
Adaptive Quality Recommendation Mechanism for Software Service Provisioning
ICWS '08 Proceedings of the 2008 IEEE International Conference on Web Services
Dynamicity vs. effectiveness: studying online clustering for scatter/gather
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
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
Scatter/Gather browsing of web service QoS data
Future Generation Computer Systems
Service selection for happy users: making user-intuitive quality abstractions
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
User-centered design of a QoS-based web service selection system
Service Oriented Computing and Applications
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In most of current research works on Quality of Service (QoS) based web service selection, searching is usually the dominant way to find the desired services. However, sometimes, requestors may not have the knowledge of the available QoS attributes and their value ranges in the registry, or they may only have vague QoS requirements. Under this situation, we believe that browsing is a more appropriate way to help the QoS-based service selection process. In this paper, we propose an interactive QoS browsing mechanism to first show an overview of the QoS value distribution to requestors and then gradually present more and more detailed views on some requestor interested value ranges. We find that interval data (or more generally symbolic data) is a more proper type to represent the QoS value, compared with the single valued numerical data. So we use interval clustering algorithms to implement our browsing system. The experiment compares the performance of using different distance measures and shows the effectiveness of the interval clustering algorithm we use. We also use a sample data set to illustrate the interactive QoS browsing process.