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Communication Dans Un Congrès Année : 2021

Semantic Data Transformation

Résumé

Data transformation from diverse formats to semantic data is a major challenge that is being addressed by commercial products available in the market to some extent. However, the transformation process still requires considerable effort from users. Knowledge creation, whichis one of the major steps in knowledge graph (KG) maintenance, needs existing data transformation from various formats to RDF (Resource Description Framework) data. Current data transformation approaches are either manual or through mappings. This work presents a semantic data transformation approach for knowledge creation that is semi-automatic requiring minimum possible input from users and does so with machine learning and natural language processing techniques.
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Dates et versions

hal-04491486 , version 1 (06-03-2024)

Identifiants

  • HAL Id : hal-04491486 , version 1

Citer

Joffrey De Oliveira, Olivier Curé, Philippe Calvez. Semantic Data Transformation. 2nd International Workshop on Deep Learning meets Ontologies and Natural Language Processing (DeepOntoNLP 2021) & 6th International Workshop on Explainable Sentiment Mining and Emotion Detection (X-SENTIMENT 2021), Jun 2021, Hersonissos, Greece. pp.39-46. ⟨hal-04491486⟩
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