DocumentCode
2701225
Title
A New Approach to Web Services Characterization
Author
Liu, Yan ; Zhuang, Mingguang ; Wang, Qingling ; Zhang, Guannan
Author_Institution
Tongji Univ., Shanghai
fYear
2008
fDate
9-12 Dec. 2008
Firstpage
404
Lastpage
409
Abstract
Service capability, which represents the actions performed or the information delivered by a service, has become an important issue for service-oriented architecture. But most of the current semantic representation methods for service capabilities are usually based on top-down methodology and there is a gap between the semantic web services approach and the real features of web services. We aim to develop services characterization methods with statistical study on existing web services and to improve services capability representation with bottom-up software services comprehension. In this paper, the main issues for statistical study on existing web services are summarized. Two types of services characterization methods are proposed in our work: quantitative statistical study which used for probing the distribution of main objects in web services and relational statistical study which used for clustering actions or contents and measuring the similarity of web services. We conducted a statistical study on more than four hundred WSDL documents collected from XMethods.net, Amazon and Google and main quantitive statistical results are presented in this paper. A statistical relational model is proposed for mining and recognizing the patterns of services.
Keywords
semantic Web; Amazon; Google; WSDL documents; XMethods.net; semantic representation methods; service-oriented architecture; statistical study; web services characterization; Embedded software; Explosives; Pattern recognition; Probes; Quality of service; Semantic Web; Service oriented architecture; Software performance; Web and internet services; Web services; Services Characterization; Statistical Relational Learning; Web Services;
fLanguage
English
Publisher
ieee
Conference_Titel
Asia-Pacific Services Computing Conference, 2008. APSCC '08. IEEE
Conference_Location
Yilan
Print_ISBN
978-0-7695-3473-2
Electronic_ISBN
978-0-7695-3473-2
Type
conf
DOI
10.1109/APSCC.2008.226
Filename
4780708
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