Using case-based reasoning for improving precision and recall in web services selection

Web services are currently one of the main technologies employed to create a systematic and extensible framework for application development. However, due to the large number of web services that exist nowadays, locating one or several web services to fulfil the functional requirements of a user or an organisation, is a complex and time consuming activity for application developers, also reducing their productivity. One possible solution for this problem is the implementation of a semantic component, structured as a library and populated with cases which represent web services in such a way that it may extend the functionality of the existing web services directories. This paper describes a model for searching and selecting web services supported by Case-Based Reasoning (CBR). Results showed that the extension to Universal Description, Discovery and Integration (UDDI) yielded 100% recall while precision improved significantly, depending some times on the way the user queried the system.

[1]  Munindar P. Singh,et al.  Engineering self-organizing referral networks for trustworthy service selection , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[2]  Mark Klein,et al.  Massachusetts Institute of Technology Abraham Bernstein University of Zurich Toward High-Precision Service Retrieval , 2022 .

[3]  Schahram Dustdar,et al.  A survey on web services composition , 2005, Int. J. Web Grid Serv..

[4]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[5]  E. Michael Maximilien,et al.  Agent-based trust model involving multiple qualities , 2005, AAMAS '05.

[6]  Mohand-Said Hacid,et al.  On automating Web services discovery , 2003, The VLDB Journal.

[7]  Tao Yu,et al.  Service Selection Algorithms for Composing Complex Services with Multiple QoS Constraints , 2005, ICSOC.

[8]  Sheila A. McIlraith,et al.  A Bottom-Up Approach to Automating Web Service Discovery, Customization, and Semantic Translation , 2003 .

[9]  Maria Luisa Villani,et al.  The C-Cube framework: developing autonomic applications through web services , 2005, ACM SIGSOFT Softw. Eng. Notes.

[10]  Munindar P. Singh,et al.  A DAML-based repository for QoS-aware semantic Web service selection , 2004, Proceedings. IEEE International Conference on Web Services, 2004..

[11]  Eleni Stroulia,et al.  Semantic Structure Matching for Assessing Web-Service Similarity , 2003, ICSOC.

[12]  Shuping Ran,et al.  A model for web services discovery with QoS , 2003, SECO.

[13]  E. Michael Maximilien,et al.  Toward autonomic web services trust and selection , 2004, ICSOC '04.

[14]  Matthias Klusch,et al.  Automated semantic web service discovery with OWLS-MX , 2006, AAMAS '06.

[15]  James A. Hendler,et al.  Filtering and selecting semantic Web services with interactive composition techniques , 2004, IEEE Intelligent Systems.

[16]  Munindar P. Singh,et al.  Agent-based service selection , 2004, J. Web Semant..

[17]  Tao Yu,et al.  Service Selection Algorithms for Web Services with End-to-End QoS Constraints , 2004, CEC.

[18]  Anne H. H. Ngu,et al.  QoS computation and policing in dynamic web service selection , 2004, WWW Alt. '04.

[19]  E. Michael Maximilien,et al.  Multiagent System for Dynamic Web Services Selection , 2005 .

[20]  E. Michael Maximilien,et al.  A framework and ontology for dynamic Web services selection , 2004, IEEE Internet Computing.

[21]  Janet L. Kolodner,et al.  Maintaining Organization in a Dynamic Long-Term Memory , 1983, Cogn. Sci..

[22]  Ellis R Bareiss.  Protos: A Unified Approach to Concept Representation, Classification, andLearning (Ph.D. Dissertation) , 1988 .

[23]  Bruce Porter,et al.  Protos: a unified approach to concept representation, classification, and learning , 1988 .

[24]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1989, IJCAI 1989.

[25]  Michael Grüninger,et al.  Towards a First-Order Ontology for Semantic Web Services , .

[26]  Lundy M. Lewis,et al.  A Case-Based Reasoning Solution to the Problem of Redundant Resolutions of Nonconformances in Large-Scale Manufacturing , 1991, IAAI.

[27]  Daniel A. Menascé,et al.  QoS Issues in Web Services , 2002, IEEE Internet Comput..

[28]  Kenneth B. Haase,et al.  Interlingual BRICO , 2000, IBM Syst. J..

[29]  Ray Bareiss,et al.  Concept Learning and Heuristic Classification in WeakTtheory Domains , 1990, Artif. Intell..

[30]  Tao Yu,et al.  The Design of QoS Broker Algorithms for QoS-Capable Web Services , 2004, Int. J. Web Serv. Res..