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URBE: Web Service Retrieval Based on Similarity Evaluation

Published: 01 November 2009 Publication History

Abstract

In this work, we present Uddi Registry By Example (Urbe), a novel approach for Web service retrieval based on the evaluation of similarity between Web service interfaces. Our approach assumes that the Web service interfaces are defined with Web Service Description Language (WSDL) and the algorithm combines the analysis of their structures and the analysis of the terms used inside them. The higher the similarity, the less are the differences among their interfaces. As a consequence, Urbe is useful when we need to find a Web service suitable to replace an existing one that fails. Especially in autonomic systems, this situation is very common since we need to ensure the self-management, the self-configuration, the self-optimization, the self-healing, and the self-protection of the application that is based on the failed Web service. A semantic-oriented variant of the approach is also proposed, where we take advantage of annotations semantically enriching WSDL specifications. Semantic Annotation for WSDL (SAWSDL) is adopted as a language to annotate a WSDL description. The Urbe approach has been implemented in a prototype that extends a Universal Description, Discovery and Integration (UDDI) compliant Web service registry.

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  • (2021)Measuring Semantic Similarity between Services Using HypergraphsThe 23rd International Conference on Information Integration and Web Intelligence10.1145/3487664.3487693(205-211)Online publication date: 29-Nov-2021
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  1. URBE: Web Service Retrieval Based on Similarity Evaluation

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    Published In

    cover image IEEE Transactions on Knowledge and Data Engineering
    IEEE Transactions on Knowledge and Data Engineering  Volume 21, Issue 11
    November 2009
    143 pages

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    IEEE Educational Activities Department

    United States

    Publication History

    Published: 01 November 2009

    Author Tags

    1. WSDL/SAWSDL
    2. Web-based services
    3. information search and retrieval
    4. similarity.

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    • (2022)Dynamic Strategies for Query Constructing and Rank Merging from Multiple Search EnginesService Oriented and Cloud Computing10.1007/978-3-319-24072-5_10(141-155)Online publication date: 10-Mar-2022
    • (2022)Automated RESTful API Service Discovery with Various Interface FeaturesService-Oriented Computing10.1007/978-3-031-20984-0_4(54-70)Online publication date: 29-Nov-2022
    • (2021)Measuring Semantic Similarity between Services Using HypergraphsThe 23rd International Conference on Information Integration and Web Intelligence10.1145/3487664.3487693(205-211)Online publication date: 29-Nov-2021
    • (2021)Improving Ocean Data Services with Semantics and Quick IndexJournal of Computer Science and Technology10.1007/s11390-021-1374-036:5(963-984)Online publication date: 1-Oct-2021
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    • (2018)Exploiting Semantic Web Services in the Development of Context-Aware SystemsProcedia Computer Science10.1016/j.procs.2018.01.137127:C(398-407)Online publication date: 1-May-2018
    • (2018)A structural-semantic web service selection approach to improve retrievability of web servicesInformation Systems Frontiers10.1007/s10796-016-9731-120:6(1319-1344)Online publication date: 1-Dec-2018
    • (2017)Semantic similarity based web services composition frameworkProceedings of the Symposium on Applied Computing10.1145/3019612.3019805(1319-1325)Online publication date: 3-Apr-2017
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