DocumentCode :
2866068
Title :
Automatic Discovery of Semantic Manufacturing Grid Services
Author :
Zhang, Lei ; Ma, Jinping ; Zhang, Song
Author_Institution :
Qingdao Univ., Qingdao
fYear :
2007
fDate :
29-31 Oct. 2007
Firstpage :
430
Lastpage :
433
Abstract :
Services in manufacturing grid (MG) are dynamically aggregated from different organizations. So it is essential for MG that services can be discovered efficiently. Automatic semantic and IR based approach of service discovery within a semantic manufacturing grid (SMG) architecture is studied in this paper. In SMG, services and job requirements are semantically described by a merged ontology of grid service ontology and manufacturing ontology. Service discovery is formalized as matchmaking between a job and advertised services. All kinds of degree of match (DoM) are formally defined considering both semantic match and document similarity. Then, a hybrid semantic and IR based matchmaking algorithm is presented. A SMG prototype system used for collaborative MEMS manufacturing has been built, in which a semantic service registry named UDDIe4SMG is built by extending UDDI and specially designed for efficient service discovery. Experiments show that the automatic service discovery approach in SMG works well and has good performance.
Keywords :
Web services; grid computing; information retrieval; intelligent manufacturing systems; ontologies (artificial intelligence); semantic Web; automatic service discovery; collaborative MEMS manufacturing; information retrieval; micro electro-mechanical system; ontology; semantic manufacturing grid service; semantic service registry; Collaborative work; Educational institutions; Feature extraction; Manufacturing automation; OWL; Ontologies; Prototypes; Pulp manufacturing; Semantic Web; Web services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantics, Knowledge and Grid, Third International Conference on
Conference_Location :
Shan Xi
Print_ISBN :
0-7695-3007-9
Electronic_ISBN :
978-0-7695-3007-9
Type :
conf
DOI :
10.1109/SKG.2007.101
Filename :
4438587
Link To Document :
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