An ant-inspired approach for semantic web service clustering

This paper presents a method inspired by ants behavior for creating clusters of semantic Web services. The clustering method groups services according to their semantic similarity. Services are grouped in the same cluster if they provide similar functionality and their input and output parameters are annotated with similar ontology concepts. We propose a matching method which evaluates the semantic similarity level between two service descriptions. The ant-based clustering method was tested and validated on the set of semantic Web services included in the SAWSDL-TC benchmark collection.

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

[2]  Yanlong Zhai,et al.  A Reflective Framework to Support Adaptive Service Composition under Correctness Constrains , 2008, 2008 Third International Conference on Internet and Web Applications and Services.

[3]  Vincenzo Grassi,et al.  Flow-Based Service Selection forWeb Service Composition Supporting Multiple QoS Classes , 2007, IEEE International Conference on Web Services (ICWS 2007).

[4]  Schahram Dustdar,et al.  Web service clustering using multidimensional angles as proximity measures , 2009, TOIT.

[5]  Richi Nayak,et al.  Web Service Discovery with additional Semantics and Clustering , 2007 .

[6]  James Dooley,et al.  Proactive Runtime Service Discovery , 2008, 2008 IEEE International Conference on Services Computing.

[7]  Anthony Kulis,et al.  Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies , 2009, Scalable Comput. Pract. Exp..

[8]  Kaijun Ren,et al.  A QSQL-based Efficient Planning Algorithm for Fully-automated Service Composition in Dynamic Service Environments , 2008, 2008 IEEE International Conference on Services Computing.

[9]  Vasant Honavar,et al.  Composing Web Services through Automatic Reformulation of Service Specifications , 2008, 2008 IEEE International Conference on Services Computing.

[10]  Yanchun Zhang,et al.  Efficiently finding web services using a clustering semantic approach , 2008, CSSSIA '08.

[11]  Mazen Malek Shiaa,et al.  An Incremental Graph-based Approach to Automatic Service Composition , 2008, 2008 IEEE International Conference on Services Computing.

[12]  Marco Dorigo,et al.  Ant-Based Clustering and Topographic Mapping , 2006, Artificial Life.

[13]  Jean-Louis Deneubourg,et al.  The dynamics of collective sorting robot-like ants and ant-like robots , 1991 .

[14]  Luiz Olavo Bonino da Silva Santos,et al.  Towards a Goal-Based Service Framework for Dynamic Service Discovery and Composition , 2009, 2009 Sixth International Conference on Information Technology: New Generations.

[15]  Verena Kantere,et al.  Efficient Semantic Web Service Discovery in Centralized and P2P Environments , 2008, SEMWEB.

[16]  Dario Floreano,et al.  Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies , 2008 .

[17]  Freddy Lécué,et al.  Optimizing Causal Link Based Web Service Composition , 2008, ECAI.