Service composition recovery using formal concept analyst & WordNet similarity

The increased number of web services and the continuous need to integrate them into complex business processes have increased the need to enhance the web service discovery and selection processes. Service discovery based on semantics of web services is one of the main needs in service integration and composition. The main current approaches for semantic discovery of services are the keyword-based approach and the ontology-based approach. The plain simple keyword matching strategy is time-consuming and has inefficient recall and precision. The ontology-based strategy, on the other hand, is efficient, but may not be practical for the wide public use due to the lack of domain experts. In this paper, we propose a new approach that support semantic service discovery and service backing up in case of service unavailability. This approach is built using the FCA ( Formal concept analysis ) lattices and the WordNet.

[1]  Guowen Wu,et al.  Web Service Discovery in Large Distributed System Incorporating Semantic Annotations , 2006, SWWS.

[2]  W. Marsden.  I and J , 2012 .

[3]  Takahiro Kawamura,et al.  Semantic Matching of Web Services Capabilities , 2002, SEMWEB.

[4]  Seema Bawa,et al.  Web Service Categorization Using Normalized Similarity Score , 2010 .

[5]  David W. Conrath,et al.  Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy , 1997, ROCLING/IJCLCLP.

[6]  T. Landauer,et al.  A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .

[7]  Graeme Hirst,et al.  Evaluating WordNet-based Measures of Lexical Semantic Relatedness , 2006, CL.

[8]  Jun Zhang,et al.  Simlarity Search for Web Services , 2004, VLDB.

[9]  Shanshan Liu,et al.  Matching Algorithm of Web Services Based on Semantic Distance , 2009 .

[10]  Wilson Wong,et al.  Web service clustering using text mining techniques , 2009, Int. J. Agent Oriented Softw. Eng..

[11]  Paul M. B. Vitányi,et al.  The Google Similarity Distance , 2004, IEEE Transactions on Knowledge and Data Engineering.

[12]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[13]  Gerd Stumme,et al.  Conceptual Knowledge Discovery and Data Analysis , 2000, ICCS.

[14]  Gina-Anne Levow,et al.  Term representation with Generalized Latent Semantic Analysis , 2007 .

[15]  Y. Amghar,et al.  Enhancing Web Service Discovery by Using Collaborative Tagging System , 2008, 2008 4th International Conference on Next Generation Web Services Practices.

[16]  Peter Willett,et al.  Readings in information retrieval , 1997 .

[17]  Peter D. Turney.  Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL , 2001, ECML.

[19]  Paul Compton,et al.  Formal Concept Analysis for Domain-Specific Document Retrieval Systems , 2001, Australian Joint Conference on Artificial Intelligence.