AZZI, Rabia; DIALLO, Abdourahmane Gayo

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AZZI, Rabia

Bordeaux population health [BPH]

DIALLO, Abdourahmane Gayo

Bordeaux population health [BPH]

Langue

Communication dans un congrès avec actes

Ce document a été publié dans

CEUR Workshop Proceedings, Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, SemTab 2020, 2020-11-05, Virtual. 2020-11-05, vol. 2775, p. 9-16

Résumé en anglais

In this paper we present AMALGAM, a matching approach to annotate tabular dataset with the use of a knowledge graph, developed in the context of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020). The ultimate goal is to provide fast and e cient approach to annotate tabular data with entities from a background knowledge. The approach combines lookup and filtering services combined with text pre-processing techniques. Experiments conducted in the context of SemTab 2020 with both Column Type Annotation and Cell Type Annotation tasks showed promising results.< Réduire

URI

https://oskar-bordeaux.fr/handle/20.500.12278/94959

Unités de recherche

Bordeaux Population Health Research Center (BPH) - UMR 1219