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Authors: Fellipe Freire ; Crishane Freire and Damires Souza

Affiliation: Federal Institute of Education and Science and Technology of Paraíba, Brazil

Keyword(s): RDF Data Conversion, Entity Type Recognition, Semi-Structured Data, JSON Documents, Semantics Usage.

Abstract: Nowadays, many Web data sources and APIs make their data available on the Web in semi-structured formats such as JSON. However, JSON data cannot be directly used in the Web of data, where principles such as URIs and semantically named links are essential. Thus it is necessary to convert JSON data into RDF data. To this end, we have to consider semantics in order to provide data reference according to domain vocabularies. To help matters, we present an approach which identifies JSON metadata, aligns them with domain vocabulary terms and converts data into RDF. In addition, along with the data conversion process, we provide the identification of the semantically most appropriate entity types to the JSON objects. We present the definitions underlying our approach and results obtained with the evaluation.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Freire, F.; Freire, C. and Souza, D. (2017). Enhancing JSON to RDF Data Conversion with Entity Type Recognition. In Proceedings of the 13th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-246-2; ISSN 2184-3252, SciTePress, pages 97-106. DOI: 10.5220/0006302900970106

@conference{webist17,
author={Fellipe Freire. and Crishane Freire. and Damires Souza.},
title={Enhancing JSON to RDF Data Conversion with Entity Type Recognition},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - WEBIST},
year={2017},
pages={97-106},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006302900970106},
isbn={978-989-758-246-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - WEBIST
TI - Enhancing JSON to RDF Data Conversion with Entity Type Recognition
SN - 978-989-758-246-2
IS - 2184-3252
AU - Freire, F.
AU - Freire, C.
AU - Souza, D.
PY - 2017
SP - 97
EP - 106
DO - 10.5220/0006302900970106
PB - SciTePress

- Science and Technology Publications, Lda.
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