Overview

This book constitutes the thoroughly refereed postproceedings of the First International Workshop on Semantic Web Services and Web Process Composition, SWSWPC 2004, held in San Diego, CA, USA in July 2004.The 9 revised full papers presented together with an introduction by the volume editors, a panel summary and the extended abstract of an invited talk were carefully selected during two rounds of reviewing and improvement.Web services and Web processes promise to ease several current Web infrastructure challenges, such as the integration of data, applications and processes. Web services are truly platform independent and allow the development of distributed loosely coupled applications, a key characteristic for the success of dynamic processes.

Full Product Details

Author:   Jorge Cardoso ,  Amit Sheth ,  Kenji Satou
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2005 ed.
Volume:   3387
Dimensions:   Width: 15.50cm , Height: 0.80cm , Length: 23.50cm
Weight:   0.530kg
ISBN:  

9783540243281

ISBN 10:   3540243283
Pages:   152
Publication Date:   31 January 2005
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

to Semantic Web Services and Web Process Composition.- Panel.- Academic and Industrial Research: Do Their Approaches Differ in Adding Semantics to Web Services?.- Talk.- Interoperability in Semantic Web Services.- Full Papers.- Bringing Semantics to Web Services: The OWL-S Approach.- A Survey of Automated Web Service Composition Methods.- Enhancing Web Services Description and Discovery to Facilitate Composition.- Compensation in the World of Web Services Composition.- Trust Negotiation for Semantic Web Services.- An Efficient Algorithm for OWL-S Based Semantic Search in UDDI.- A Semantic Approach for Designing E-Business Protocols.- Towards Automatic Discovery of Web Portals.- METEOR-S Web Service Annotation Framework with Machine Learning Classification.

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