Discovering Semantic Web Services via Advanced Graph-based Matching

被引:0
作者
Cuzzocrea, Alfredo [1 ,2 ]
Fisichella, Marco [3 ]
机构
[1] ICAR CNR, Cosenza, Italy
[2] Univ Calabria, I-87030 Commenda Di Rende, Italy
[3] L3S Res Ctr, Hannover, Germany
来源
2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2011年
关键词
Composite OWL-S processes; Web service discovery; Graph matching;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the main advantages of Web services is that they can be composed into more complex processes in order to achieve a given business goal. However, such potentiality cannot be fully exploited until suitable methods and techniques allowing us to enable automatic discovery of composed processes are provided. Indeed, nowadays service discovery still focuses on matching atomic services by typically checking the similarity of functional parameters, such as inputs and outputs. However, a more profitable process discovering can be reached if both internal structure and component services are taken into account. Based on this main intuition, in this paper we describe a method for discovering composite OWL-S processes that founds on the following main contributions: (i) proposing a graph-based representation of composite OWL-S processes; and (ii) introducing an algorithm that matches over such (graph-based) representations and computes their degree of matching via combining the similarity of the atomic services they comprise and the similarity of the control flow among them. Finally, as another contribution of our research, we conducted a comprehensive experimental campaign where we tested our proposed algorithm by deriving insightful trade-offs of benefits and limitations of the overall framework for discovering Semantic Web services.
引用
收藏
页码:608 / 615
页数:8
相关论文
共 20 条
[1]  
[Anonymous], 1979, Computers and Intractablity: A Guide to the Theory of NP-Completeness
[2]  
Bellur U, 2007, 2007 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES, PROCEEDINGS, P86
[3]   A graph distance metric based on the maximal common subgraph [J].
Bunke, H ;
Shearer, K .
PATTERN RECOGNITION LETTERS, 1998, 19 (3-4) :255-259
[4]  
Burstein M., 2004, OWL S SEMANTIC MARKU
[5]  
Cardoso J, 2006, SCW 2006: IEEE SERVICES COMPUTING WORKSHOPS, PROCEEDINGS, P183
[6]  
Dong X., 2004, Proceedings of the 30th International Conference on Very Large Data Bases (VLDB'04), V30, P372, DOI DOI 10.1016/B978-012088469-8.50035-8
[7]  
Fagin R, 2003, SIAM PROC S, P28
[8]  
Gil Y, 2009, K-CAP'09: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON KNOWLEDGE CAPTURE, P121
[9]  
Goderis A, 2006, ICWS 2006: IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES, PROCEEDINGS, P312
[10]  
Kaufer F., 2006, P EUR C WEB SERV, P161, DOI [10.1109/ECOWS.2006.39, DOI 10.1109/ECOWS.2006.39]