Predicting the possibilistic score of OWL axioms through modified support vector clustering - researchr publication related

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Dario Malchiodi, Andrea G. B. Tettamanzi. Predicting the possibilistic score of OWL axioms through modified support vector clustering. In Hisham M. Haddad, Roger L. Wainwright, Richard Chbeir, editors, Proceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018, Pau, France, April 09-13, 2018. pages 1984-1991, ACM, 2018. [doi]

The following publications are possibly variants of this publication:

Predicting the Possibilistic Score of OWL Axioms Through Support Vector RegressionDario Malchiodi, Célia da Costa Pereira, Andrea G. B. Tettamanzi. sum 2018: 380-386 [doi]

Predicting the Score of Atomic Candidate OWL Class AxiomsAli Ballout, Andrea G. B. Tettamanzi, Célia da Costa Pereira. webi 2022: 72-79 [doi]

Possibilistic testing of OWL axioms against RDF dataAndrea G. B. Tettamanzi, Catherine Faron-Zucker, Fabien Gandon. ijar, 91:114-130, 2017. [doi]

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