@inproceedings{RigBelLamZes12-URSW12-IW,
author = {Fabrizio Riguzzi and Elena Bellodi and Evelina Lamma and Riccardo Zese},
title = {Epistemic and Statistical Probabilistic Ontologies},
booktitle = {Proceedings of the 8th International Workshop on Uncertain Reasoning for the Semantic Web (URSW2012), Boston, USA, 11 November 2012},
year = {2012},
editor = {Fernando Bobillo and
Rommel Carvalho and
da Costa, Paulo C. G. and
Nicola Fanizzi and
Laskey, Kathryn B. and
Laskey, Kenneth J. and
Thomas Lukasiewicz and
Trevor Martin and
Matthias Nickles and
Michael Pool},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
address = {Aachen, Germany},
number = {900},
pages = {3-14},
pdf = {http://ceur-ws.org/Vol-900/paper1.pdf},
abstract = {We present DISPONTE, a semantics for probabilistic ontologies that is based on the distribution semantics for probabilistic logic programs. In DISPONTE the axioms of a probabilistic ontology can be
annotated with an epistemic or a statistical probability. The epistemic probability represents a degree of confidence in the axiom, while the statistical probability considers the populations to which the axiom is applied.}
}
@inproceedings{RigBelLamZese12-PAI12-NW,
title = {Semantics and Inference for Probabilistic Ontologies},
pages = { 41-46},
author = {Fabrizio Riguzzi and Evelina Lamma and Elena Bellodi and Riccardo Zese},
editor = {Matteo Baldoni and Federico Chesani and Bernardo Magnini and Paola Mello and Marco Montali},
booktitle = { Popularize Artificial Intelligence. Proceedings of the AI*IA Workshop and Prize for Celebrating 100th Anniversary of Alan Turing's Birth ({PAI 2012}), Rome, Italy, June 15, 2012},
copyright = {by the authors},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
address = {Aachen, Germany},
volume = {860},
year = {2012},
pdf = {http://ceur-ws.org/Vol-860/paper3.pdf}
}
@inproceedings{BufLamRigFor12-PAI12-NW,
title = {Un sistema di Vision Inspection basato su reti neurali},
author = {Ludovico Buffon and Evelina Lamma and Fabrizio Riguzzi and Davide Formenti},
pages = { 1-6},
editor = {Matteo Baldoni and Federico Chesani and Bernardo Magnini and Paola Mello and Marco Montai},
booktitle = { Popularize Artificial Intelligence. Proceedings of the AI*IA Workshop and Prize for Celebrating 100th Anniversary of Alan Turing's Birth ({PAI 2012}), Rome, Italy, June 15, 2012},
copyright = {by the authors},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
address = {Aachen, Germany},
volume = {860},
year = {2012},
pdf = {http://ceur-ws.org/Vol-860/paper9.pdf}
}
@inproceedings{RigBelLam12-DL12-IW,
author = {Fabrizio Riguzzi and Elena Bellodi and Evelina Lamma},
title = {Probabilistic {Datalog+/-} under the Distribution Semantics},
booktitle = {Proceedings of the 25th International Workshop on Description Logics ({DL2012}),
Roma, Italy, 7-10 June 2012},
editor = {Yevgeny Kazakov and Domenico Lembo and Frank Wolter},
year = {2012},
abstract = {We apply the distribution semantics for probabilistic ontologies (named DISPONTE) to the Datalog+/- language.
In DISPONTE the formulas of a probabilistic ontology can be annotated with an epistemic or a statistical probability. The epistemic probability represents a degree of confidence in the formula, while the statistical probability considers the populations to which the formula is applied.
The probability of a query is defined in terms of finite set of finite explanations for the query, where an explanation is a set of possibly instantiated formulas that is sufficient for entailing the query.
The probability of a query is computed from the set of explanations by making them mutually exclusive.
We also compare the DISPONTE approach for Datalog+/- ontologies with that of Probabilistic Datalog+/-, where an ontology is composed of a Datalog+/- theory whose formulas are associated to an assignment of values for the random variables of a companion Markov Logic Network.
},
copyright = {by the authors},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
address = {Aachen, Germany},
url = {http://ml.unife.it/wp-content/uploads/Papers/RigBelLam12-DL12.pdf},
pdf = {http://ceur-ws.org/Vol-846/paper_25.pdf},
volume = {846},
pages = {519-529}
}
@inproceedings{RigBelLam12-CILC12-NC,
author = {Fabrizio Riguzzi and Elena Bellodi and Evelina Lamma},
title = {Probabilistic Ontologies in {Datalog+/-}},
booktitle = {Proceedings of the 27th Italian Conference on Computational Logic ({CILC2012}),
Roma, Italy, 6-7 June 2012},
year = {2012},
abstract = {In logic programming the distribution semantics is one of the most popular approaches for dealing with uncertain information. In this paper
we apply the distribution semantics to the Datalog+/- language that is grounded in logic programming and allows tractable ontology querying. In the resulting semantics, called DISPONTE, formulas of a probabilistic ontology can be annotated with an epistemic or a statistical probability. The epistemic probability represents a degree of confidence in the formula, while the statistical probability considers the populations to which the formula is applied.
The probability of a query is defined in terms of finite set of finite explanations for the query.
We also compare the DISPONTE approach for Datalog+/- ontologies with that of Probabilistic Datalog+/- where an ontology is composed of a Datalog+/- theory whose formulas are associated to an assignment of values for the random variables of a companion Markov Logic Network.
},
copyright = {by the authors},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
volume = {857},
address = {Aachen, Germany},
url = {http://ml.unife.it/wp-content/uploads/Papers/RigBelLam12-CILC12.pdf},
pdf = {http://ceur-ws.org/Vol-857/paper_f16.pdf},
pages = {221-235}
}
@incollection{AlbGavLam12-LPNA-BC,
author = {Alberti, Marco and Gavanelli, Marco and Lamma, Evelina},
title = {Deon+: Abduction and Constraints for Normative Reasoning},
booktitle = {Logic Programs, Norms and Action},
series = {Lecture Notes in Computer Science},
editor = {Artikis, Alexander and Craven, Robert and Kesim Cicekli, Nihan and Sadighi, Babak and Stathis, Kostas},
publisher = {Springer Berlin / Heidelberg},
isbn = {978-3-642-29413-6},
keyword = {Computer Science},
pages = {308-328},
volume = 7360,
url = {http://dx.doi.org/10.1007/978-3-642-29414-3\_17},
note = {10.1007/978-3-642-29414-3\_17},
abstract = {Deontic concepts and operators have been widely used in several fields where representation of norms is needed, including legal reasoning and normative multi-agent systems. In the meantime, abductive logic programming (ALP for short) has been exploited to formalize societies of agents, commitments and institutions, taking advantage from ALP operational support as (static or dynamic) verification tool. Nonetheless, the modal nature of deontic operators smoothly fits into abductive semantics and abductive reasoning, where hypotheses can be raised at run-time on the basis of the specified formulas. In recent works, a mapping of the most common deontic operators (obligation, prohibition, permission) to the abductive expectations of an ALP framework for agent societies has been proposed. This mapping was supported by showing a correspondence between declarative semantics of abductive expectations and Kripke semantics for deontic operators. Building upon such correspondence, in this work we introduce Deon + , a language where the two basic deontic operators (namely, obligation and prohibition) are enriched with quantification over time, by means of ALP and Constraint Logic Programming (CLP for short). In this way, we can take into account different flavors for obligations and prohibitions over time, i.e., existential or universal. We also discuss how to address consistency verification of such deontic specifications by a suitable ALP proof procedure, enriched with CLP constraints.},
year = 2012
}
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