Contextual service discovery using term expansion and binding coverage analysis

Business cloud emerges as a new solution for providing on-demand business services over Internet. Standardized service technologies drive widespread adoption of clouds and enable computation evolution towards service-oriented paradigm. While diversified cloud services are readily available today, how to discover desired services fitting into user's context becomes a practical challenge. In this paper, we propose a Contextual Service Discovery (CSD) approach to help find out qualified services in accordance with binding context on the user side. Query descriptions and binding information are analyzed as a set of meaningful terms. We designed a term expansion mechanism to improve matchmaking performance by mitigating issues of wording bias and ambiguity. Besides, binding coverage analysis between multiple services and a given query is conducted to ensure that matched services are compatible with user's contextual expectation. The experimental results show that the proposed approach is with better performance than other alternatives under Top- N precision and recall metrics. We propose a contextual approach to discovering web services.The approach mitigates issues of wording bias and ambiguity by term expansion.The approach ensures that discovered services are compatible with binding context.The approach can find out qualified services for constructing a composite service.

[1]  Dieter Fensel,et al.  Automatic Location of Services , 2005, ESWC.

[2]  Rajkumar Buyya,et al.  Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .

[3]  Eleni Stroulia,et al.  Structural and Semantic Matching for Assessing Web-service Similarity , 2005, Int. J. Cooperative Inf. Syst..

[4]  Jonathan Lee,et al.  Dynamic Service Composition: a Discovery-Based Approach , 2008, Int. J. Softw. Eng. Knowl. Eng..

[5]  Euripides G. M. Petrakis,et al.  Semantic similarity methods in wordNet and their application to information retrieval on the web , 2005, WIDM '05.

[6]  Schahram Dustdar,et al.  A survey on context-aware web service systems , 2009, Int. J. Web Inf. Syst..

[7]  Yanchun Zhang,et al.  Web services discovery and rank: An information retrieval approach , 2010, Future Gener. Comput. Syst..

[8]  Xu Ke,et al.  A kernel based structure matching for web services search , 2007, WWW 2007.

[9]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[10]  Amit P. Sheth,et al.  Discovery of Web services in a federated registry environment , 2004 .

[11]  Dieter Fensel,et al.  A Logical Framework for Web Service Discovery , 2004, SWS@ISWC.

[12]  Barbara Pernici,et al.  URBE: Web Service Retrieval Based on Similarity Evaluation , 2009, IEEE Transactions on Knowledge and Data Engineering.

[13]  Michael Schrefl,et al.  Analysis of business process integration in Web service context , 2007, Future Gener. Comput. Syst..

[14]  Deborah L. McGuinness,et al.  Bringing Semantics to Web Services with OWL-S , 2007, World Wide Web.

[15]  Kecheng Liu,et al.  A Survey of Context Aware Web Service Discovery: From User's Perspective , 2010, 2010 Fifth IEEE International Symposium on Service Oriented System Engineering.

[16]  Amit P. Sheth,et al.  METEOR-S WSDI: A Scalable P2P Infrastructure of Registries for Semantic Publication and Discovery of Web Services , 2005, Inf. Technol. Manag..

[17]  Brahim Medjahed,et al.  Context-based matching for Web service composition , 2007, Distributed and Parallel Databases.

[18]  Antonio Corradi,et al.  The management of cloud systems , 2014, Future Gener. Comput. Syst..

[19]  Mara Nikolaidou,et al.  A Specialized Search Engine for Web Service Discovery , 2012, 2012 IEEE 19th International Conference on Web Services.

[20]  Andrea Zisman,et al.  A Platform for Context Aware Runtime Web Service Discovery , 2007, IEEE International Conference on Web Services (ICWS 2007).

[21]  Zibin Zheng,et al.  WSExpress: A QoS-aware Search Engine for Web Services , 2010, 2010 IEEE International Conference on Web Services.

[22]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[23]  Jayant Madhavan,et al.  Mining structures for semantics , 2004, SKDD.

[24]  Jerry R. Hobbs,et al.  DAML-S: Semantic Markup for Web Services , 2001, SWWS.

[25]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[26]  Shang-Pin Ma,et al.  Dynamic Service Composition Using Core Service Identification , 2014, J. Inf. Sci. Eng..

[27]  Stuart E. Middleton,et al.  A business-oriented Cloud federation model for real-time applications , 2012, Future Gener. Comput. Syst..

[28]  David McLean,et al.  An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources , 2003, IEEE Trans. Knowl. Data Eng..

[29]  Hinrich Schütze,et al.  Introduction to information retrieval , 2008 .