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Automated and Explainable Ontology Extension Based on Deep Learning: A
  Case Study in the Chemical Domain

Automated and Explainable Ontology Extension Based on Deep Learning: A Case Study in the Chemical Domain

19 September 2021
A. Memariani
Martin Glauer
Fabian Neuhaus
Till Mossakowski
Janna Hastings
ArXivPDFHTML

Papers citing "Automated and Explainable Ontology Extension Based on Deep Learning: A Case Study in the Chemical Domain"

4 / 4 papers shown
Title
Using Artificial Neural Networks to Determine Ontologies Most Relevant
  to Scientific Texts
Using Artificial Neural Networks to Determine Ontologies Most Relevant to Scientific Texts
Lukáš Korel
Alexander S. Behr
N. Kockmann
M. Holeňa
6
0
0
17 Sep 2023
Ontology Development is Consensus Creation, Not (Merely) Representation
Ontology Development is Consensus Creation, Not (Merely) Representation
Fabian Neuhaus
Janna Hastings
13
15
0
21 Oct 2022
When one Logic is Not Enough: Integrating First-order Annotations in OWL
  Ontologies
When one Logic is Not Enough: Integrating First-order Annotations in OWL Ontologies
Simon Flügel
Martin Glauer
Fabian Neuhaus
Janna Hastings
13
7
0
07 Oct 2022
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
239
31,257
0
16 Jan 2013
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