Predicting the top-level ontological concepts of domain entities using word embeddings, informal definitions, and deep learning-Reference-Cited by-同舟云学术

Predicting the top-level ontological concepts of domain entities using word embeddings, informal definitions, and deep learning

Published:2022-10 Issue: Volume:203 Page:117291
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Lopes Alcides Gonçalves^ORCID,Carbonera Joel Luis,Schimidt Daniela,Abel Mara^ORCID

Funder

Petrobras

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference27 articles.

1. Abel, M., Perrin, M., Carbonera, J., & Garcia, L. (0000). (n.d.). Ontologies and data models: essential properties and data modeling for petroleum exploration.

2. Building ontologies with basic formal ontology;Arp,2015

3. A survey of ontology learning techniques and applications;Asim;Database,2018

4. Enriching word vectors with subword information;Bojanowski;Transactions of the Association for Computational Linguistics,2017

5. API design for machine learning software: experiences from the scikit-learn project;Buitinck,2013

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