WSEAS Transactions on Information Science and Applications


Print ISSN: 1790-0832
E-ISSN: 2224-3402

Volume 15, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


On Improving SPARQL Information Retrieval System for Semantic Internet of Things Applications

AUTHORS: Abdulrahman Jalal Ebrahim, Karim Kamoun, Sofiane Ouni, Bassam A. Zafar

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ABSTRACT: Due to the huge volume of information and knowledge derived from IoT devices, it will be hard to explore all knowledge coming from these devices. The semantic ontology-based descriptions with the semantic web are one of the most interesting ways to extract the required knowledge. However, the information retrieval typically made by the SPARQL querying language stills hard to write correct queries from what the users need as knowledge to extract. It needs a deep knowledge of the semantic information system structure. In this paper, we have developed a new correction and relaxation approach based on structural semantic similarity measure to overcome the semantic errors in SPARQL queries. This approach is applied to semantic information systems using OWL and RDF ontologies which are related to IoT applications. To achieve the efficiency of our proposal, we have developed a SPARQL querying tools. According to the queries made on IoT applications, our approach performs best results regarding the precision of the answer to these queries

KEYWORDS: Information Retrieval, semantic similarity, Internet of Things, SPARQL

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WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 15, 2018, Art. #12, pp. 107-117


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