caa a22 4500 606229035 CHVBK 20210128101206.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s10796-014-9525-2 doi (NATIONALLICENCE)springer-10.1007/s10796-014-9525-2 Service discovery acceleration with hierarchical clustering [Elektronische Daten] [Zijie Cong, Alberto Fernandez, Holger Billhardt, Marin Lujak] This paper presents an efficient Web Service Discovery approach based on hierarchical clustering. Conventional web service discovery approaches usually organize the service repository in a list manner, therefore service matchmaking is performed with linear complexity. In this work, services in a repository are clustered using hierarchical clustering algorithms with a distance measure from an attached matchmaker. Service discovery is then performed over the resulting dendrogram (binary tree). In comparison with conventional approaches that mostly perform exhaustive search, we show that service-clustering method brings a dramatic improvement on time complexity with an acceptable loss in precision. Springer Science+Business Media New York, 2014 Service discovery nationallicence Hirerachical clustering nationallicence Service matchmaking nationallicence Cong Zijie Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut Fernandez Alberto Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut Billhardt Holger Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut Lujak Marin Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut Information Systems Frontiers Springer US; http://www.springer-ny.com 17/4(2015-08-01), 799-808 1387-3326 17:4<799 2015 17 10796 https://doi.org/10.1007/s10796-014-9525-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10796-014-9525-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cong Zijie Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut NATIONALLICENCE 700 1- Fernandez Alberto Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut NATIONALLICENCE 700 1- Billhardt Holger Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut NATIONALLICENCE 700 1- Lujak Marin Artificial Intelligence Research Group, University Rey Juan Carlos, Calle Tulipan s/n, Mostoles, Madrid, Spain aut NATIONALLICENCE 773 0- Information Systems Frontiers Springer US; http://www.springer-ny.com 17/4(2015-08-01), 799-808 1387-3326 17:4<799 2015 17 10796