Search Results for author: Ana Ozaki

Found 12 papers, 0 papers with code

Extracting Rules from Neural Networks with Partial Interpretations

no code implementations1 Apr 2022 Cosimo Persia, Ana Ozaki

We investigate the problem of extracting rules, expressed in Horn logic, from neural network models.

Learning Description Logic Ontologies. Five Approaches. Where Do They Stand?

no code implementations2 Apr 2021 Ana Ozaki

The quest for acquiring a formal representation of the knowledge of a domain of interest has attracted researchers with various backgrounds into a diverse field called ontology learning.

Inductive logic programming Learning Theory

On the Complexity of Learning Description Logic Ontologies

no code implementations25 Mar 2021 Ana Ozaki

Ontologies are a popular way of representing domain knowledge, in particular, knowledge in domains related to life sciences.

Learning Theory

Automated Reasoning in Temporal DL-Lite

no code implementations17 Aug 2020 Sabiha Tahrat, German Braun, Alessandro Artale, Marco Gario, Ana Ozaki

This paper investigates the feasibility of automated reasoning over temporal DL-Lite (TDL-Lite) knowledge bases (KBs).


On the Learnability of Possibilistic Theories

no code implementations6 May 2020 Cosimo Persia, Ana Ozaki

We investigate learnability of possibilistic theories from entailments in light of Angluin's exact learning model.

Provenance for the Description Logic ELHr

no code implementations21 Jan 2020 Camille Bourgaux, Ana Ozaki, Rafael Peñaloza, Livia Predoiu

We address the problem of handling provenance information in ELHr ontologies.

Learning Query Inseparable ELH Ontologies

no code implementations17 Nov 2019 Ana Ozaki, Cosimo Persia, Andrea Mazzullo

', with A an arbitrary data instance and q and query in Q.

Enriching Ontology-based Data Access with Provenance (Extended Version)

no code implementations1 Jun 2019 Diego Calvanese, Davide Lanti, Ana Ozaki, Rafael Penaloza, Guohui Xiao

In particular, we investigate the problems of (i) deciding whether a provenance annotated OBDA instance entails a provenance annotated conjunctive query, and (ii) computing a polynomial representing the provenance of a query entailed by a provenance annotated OBDA instance.

Learning Ontologies with Epistemic Reasoning: The EL Case

no code implementations8 Feb 2019 Ana Ozaki, Nicolas Troquard

We investigate the problem of learning description logic ontologies from entailments via queries, using epistemic reasoning.

Exact Learning of Lightweight Description Logic Ontologies

no code implementations20 Sep 2017 Boris Konev, Carsten Lutz, Ana Ozaki, Frank Wolter

We study the problem of learning description logic (DL) ontologies in Angluin et al.'s framework of exact learning via queries.

New Steps on the Exact Learning of CNF

no code implementations10 Sep 2016 Montserrat Hermo, Ana Ozaki

A major problem in computational learning theory is whether the class of formulas in conjunctive normal form (CNF) is efficiently learnable.

Learning Theory

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