Semantic-Enabled and Hypermedia-Driven Linked Service Discovery
| Autor: | Michael Mrissa, Youssef Amghar, Mahdi Bennara |
|---|---|
| Přispěvatelé: | Service Oriented Computing (SOC), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Ameur, Yamine Aït |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Information retrieval
Exploit Computer science Rank (computer programming) Service discovery Hypermedia 0102 computer and information sciences 02 engineering and technology 01 natural sciences law.invention Resource (project management) 010201 computation theory & mathematics law 020204 information systems 0202 electrical engineering electronic engineering information engineering Key (cryptography) [INFO]Computer Science [cs] Semantic Web |
| Zdroj: | Model and Data Engineering-6th International Conference, MEDI 2016, Almeria, Spain, September 21-23, 2016, Proceedings Model and Data Engineering-6th International Conference, MEDI 2016, Almeria, Spain, September 21-23, 2016, Proceedings, Sep 2016, Almeria, Spain. pp.108-117, ⟨10.1007/978-3-319-45547-1_9⟩ Model and Data Engineering ISBN: 9783319455464 MEDI |
| DOI: | 10.1007/978-3-319-45547-1_9⟩ |
| Popis: | International audience; Automating discovery and composition of RESTful services with the help of semantic Web technologies is a key challenge to exploit today's Web potential. In this paper, we show how semantic annotations on resource descriptions can drive discovery algorithms on the Web. We propose a semantically-enabled variant of the BFS discovery algorithm that aims at minimizing the number of links explored while maximizing result diversity. Our algorithm calculates semantic distances between resource descriptions and user request concepts to rank explored resources accordingly. We demonstrate the applicability of our solution with a typical scenario and provide an evaluation with a prototype. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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