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Improving semantic Web services discovery and ranking: A lightweight, integrated approach

Opened Access Improving semantic Web services discovery and ranking: A lightweight, integrated approach

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Autor: García Rodríguez, José María
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2016
Publicado en: AI Communications, 29 (1), 215-217.
Tipo de documento: Artículo
Resumen: Semantic Web services frameworks provide the means to automatically discover, rank, compose and invoke services according to user requirements and preferences. However, current preference models offer limited expressiveness and they are tightly coupled with underlying discovery and ranking mechanisms. Furthermore, these mechanisms present performance, interoperability and integration issues that prevent the uptake of semantic technologies in these scenarios. In this work, we discuss three interrelated contributions on preference modeling, discovery optimization, and flexible, integrated ranking, tackling specifically the identified challenges on those areas using a lightweight approach.
Cita: García Rodríguez, J.M. (2016). Improving semantic Web services discovery and ranking: A lightweight, integrated approach. AI Communications, 29 (1), 215-217.
Tamaño: 257.7Kb
Formato: PDF

URI: http://hdl.handle.net/11441/67604

DOI: 10.3233/AIC-140644

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