Claudia d'Amato
Citata da
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Knowledge graphs
A Hogan, E Blomqvist, M Cochez, C d’Amato, GD Melo, C Gutierrez, ...
ACM Computing Surveys (Csur) 54 (4), 1-37, 2021
DL-FOIL concept learning in description logics
N Fanizzi, C d’Amato, F Esposito
Inductive Logic Programming: 18th International Conference, ILP 2008 Prague …, 2008
Anisa Rula, Lukas Schmelzeisen, Juan F. Sequeda, Steffen Staab, and Antoine Zimmermann
A Hogan, E Blomqvist, M Cochez, C d’Amato, G De Melo, C Gutierrez, ...
Knowledge graphs. CoRR, abs/2003.02320, 2020
Mining the Semantic Web: Statistical learning for next generation knowledge bases
A Rettinger, U Lösch, V Tresp, C d’Amato, N Fanizzi
Data Mining and Knowledge Discovery 24, 613-662, 2012
A semantic similarity measure for expressive description logics
C d'Amato, N Fanizzi, F Esposito
arXiv preprint arXiv:0911.5043, 2009
The data mining optimization ontology
CM Keet, A Ławrynowicz, C d’Amato, A Kalousis, P Nguyen, R Palma, ...
Journal of web semantics 32, 43-53, 2015
On the influence of description logics ontologies on conceptual similarity
C d’Amato, S Staab, N Fanizzi
International Conference on Knowledge Engineering and Knowledge Management …, 2008
Query answering and ontology population: An inductive approach
C d’Amato, N Fanizzi, F Esposito
European semantic web conference, 288-302, 2008
A dissimilarity measure for ALC concept descriptions
C d'Amato, N Fanizzi, F Esposito
Proceedings of the 2006 ACM symposium on Applied computing, 1695-1699, 2006
Tractable reasoning with Bayesian description logics
C d’Amato, N Fanizzi, T Lukasiewicz
Scalable Uncertainty Management: Second International Conference, SUM 2008 …, 2008
Conceptual clustering and its application to concept drift and novelty detection
N Fanizzi, C d’Amato, F Esposito
The Semantic Web: Research and Applications: 5th European Semantic Web …, 2008
Inductive learning for the semantic web: what does it buy?
C d'Amato, N Fanizzi, F Esposito
Semantic Web 1 (1-2), 53-59, 2010
Statistical learning for inductive query answering on OWL ontologies
N Fanizzi, C d’Amato, F Esposito
The Semantic Web-ISWC 2008: 7th International Semantic Web Conference, ISWC …, 2008
Ontology enrichment by discovering multi-relational association rules from ontological knowledge bases
C d'Amato, S Staab, AGB Tettamanzi, TD Minh, F Gandon
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 333-338, 2016
Induction of concepts in web ontologies through terminological decision trees
N Fanizzi, C d’Amato, F Esposito
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
Classification of symbolic objects: A lazy learning approach
A Appice, C d'Amato, F Esposito, D Malerba
Intelligent Data Analysis 10 (4), 301-324, 2006
Concept learning
J Lehmann, N Fanizzi, L Bühmann, C d’Amato
Perspectives on ontology learning 18, 71-91, 2014
A declarative kernel for concept descriptions
N Fanizzi, C d’Amato
International Symposium on Methodologies for Intelligent Systems, 322-331, 2006
Machine learning for the semantic web: Lessons learnt and next research directions
C d’Amato
Semantic Web 11 (1), 195-203, 2020
Reasoning by Analogy in Description Logics Through Instance-based Learning.
C d'Amato, N Fanizzi, F Esposito
SWAP, 2006
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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