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Aggregated Search of Data and Services

Abstract : The last years witnessed the success of the Linked Open Data (LOD) project as well as a significantly growing amount of semantic data sources available on the web. However, there are still a lot of data not being published as fully materialized knowledge bases like as sensor data, dynamic data, data with limited access patterns, etc. Such data is in general available through web APIs or web services. Integrating such data to the LOD or in mashups would have a significant added value. However, discovering such services requires a lot of efforts from developers and a good knowledge of the existing service repositories that the current service discovery systems do not efficiently overcome.In this thesis, we propose novel approaches and frameworks to search for semantic web services from a data integration perspective. Firstly, we introduce LIDSEARCH, a SPARQL-driven framework to search for linked data and semantic web services. Moreover, we propose an approach to enrich semantic service descriptions with Input-Output relations from ontologies to facilitate the automation of service discovery and composition. To achieve such a purpose, we apply natural language processing techniques and deep-learning-based text similarity techniques to leverage I/O relations from text to ontologies.We validate our work with proof-of-concept frameworks and use OWLS-TC as a dataset for conducting our experiments on service search and enrichment.
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Submitted on : Thursday, September 6, 2018 - 3:39:11 PM
Last modification on : Wednesday, October 14, 2020 - 3:58:20 AM
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  • HAL Id : tel-01869604, version 1


Mohamed Lamine Mouhoub. Aggregated Search of Data and Services. Web. Université Paris sciences et lettres, 2017. English. ⟨NNT : 2017PSLED066⟩. ⟨tel-01869604⟩



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