Title :
Leveraging Fragmental Semantic Data to Enhance Services Discovery
Author :
Wang, Jian ; Zhang, Jia ; Hung, Patrick C K ; Li, Zheng ; Liu, Jianxiao ; He, Keqing
Author_Institution :
State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China
Abstract :
As one foundational technology of cloud computing, services computing is playing a critical role to enable provisioning of software as a service (SaaS). However, how to effectively and efficiently discover proper available services from the cloud of resources remains a big challenge. This paper reports our continuous efforts on semantic services discovery. We extend the Support Vector Machine (SVM)-based text clustering technique in the context of service-oriented categorization in a service repository, and propose an iterative process to incrementally enrich domain ontology. A popular Web 2.0 mashup platform is used as a testbed; and preliminary evaluation results are reported.
Keywords :
cloud computing; pattern clustering; support vector machines; text analysis; SVM-based text clustering; SaaS; Web 2.0; cloud computing; domain ontology; fragmental semantic data; iterative process; service repository; services computing; services discovery enhancement; software as a service; support vector machine; Equations; Frequency domain analysis; Ontologies; Semantics; Support vector machines; Unified modeling language; Vectors;
Conference_Titel :
High Performance Computing and Communications (HPCC), 2011 IEEE 13th International Conference on
Conference_Location :
Banff, AB
Print_ISBN :
978-1-4577-1564-8
Electronic_ISBN :
978-0-7695-4538-7
DOI :
10.1109/HPCC.2011.149
