Publications
“Emotion recognition from speech based on relevant feature and majority voting”, in ICIEV, 2014.
06850685.pdf (675.21 KB)
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“Modeling OWL with Rules: The ROWL Protege Plugin”, Kobe, Japan, 2016.
ROWL.pdf (184.79 KB)
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“OWLAx: A Protege Plugin to Support Ontology Axiomatization through Diagramming”, Kobe, Japan, 2016.
OWLAx.pdf (609.13 KB)
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“Explaining Trained Neural Networks with Semantic Web Technologies: First Steps”, Twelveth International Workshop on Neural-Symbolic Learning and Reasoning, NeSy. London, UK, 2017.
2017-nesy-xai.pdf (2.09 MB)
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“Relating Input Concepts to Convolutional Neural Network Decisions”, NIPS 2017 Workshop: Interpreting, Explaining and Visualizing Deep Learning, NIPS IEVDL 2017. NIPS, CA, USA, 2017.
Relating Input Concepts to Convolutional Neural Network Decisions.pdf (2.35 MB)
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“Rule-based OWL Modeling with ROWLTab Protege Plugin”. 2017.
main.pdf (423.27 KB)
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“Reasoning over RDF Knowledge Bases using Deep Learning”, arXiv preprint arXiv:1811.04132, 2018.
, “Efficient Concept Induction for Description Logics”, in AAAI Conference on Artificial Intelligence, Honolulu, US, 2019, vol. 33.
Efficient Concept Induction for Description Logics.pdf (288.86 KB)
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“Counterfactual reasoning over large-scale human performance optimization experiments”, Virtual poster presented at the annual meeting of the Psychonomic Society, November 2020. 2020.
, “Neural-Symbolic Integration and the Semantic Web”, Semantic Web, vol. 11, no. 1, 2020.
, “Wikipedia Knowledge Graph for Explainable AI”, in Second Iberoamerican Knowledge Graphs and Semantic Web Conference (KGSWC), 2020.
2020_Wiki_KG_kgswc_conference.pdf (1.02 MB)
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“Expressibility of OWL Axioms with Patterns”, in The Semantic Web – 18th International Conference, ESWC 2021, 2021, pp. 230-245.
2021-ESWC-Expressebility-of-owl-axioms-and-patterns.pdf (357.95 KB)
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“Expressibility of OWL Axioms with Patterns”, in ESWC 2021, 2021.
Expressibility_of_OWL_ Axioms_with_Patterns.pdf (357.95 KB)
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“Neuro-Symbolic Deductive Reasoning for Cross-Knowledge Graph Entailment”, in AAAI-MAKE 2021, 2021.
2021-AAAI_MAKE.pdf (753.28 KB)
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“Neural Fuzzy Extractors: A Secure Way to Use Artificial Neural Networks for Biometric User Authentication”, Proceedings of Privacy Enhancing Technologies , vol. 2022 (4), pp. 86-104, 2022.
2020-arxiv-nfes.pdf (408.14 KB)
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