@proceedings{AIXIA2015-EB,
title = {AI*IA 2015, Advances in Artificial Intelligence, XIVth International Conference of the Italian Association for Artificial Intelligence, Ferrara, Italy, September 23-25, 2015, Proceedings},
year = 2015,
editor = {Marco Gavanelli and Evelina Lamma and Fabrizio Riguzzi},
volume = {9336},
publisher = {Springer International Publishing},
address = {Heidelberg, Germany},
series = {Lecture Notes in Computer Science},
issn = {0302-9743},
url = {http://link.springer.com/book/10.1007%2F978-3-319-24309-2},
venue = {Ferrara, Italy},
eventdate = {September 23-25, 2015},
copyright = {Springer International Publishing Switzerland},
printisbn = {978-3-319-24308-5},
onlineisbn = {978-3-319-24309-2},
doi = {10.1007/978-3-319-24309-2}
}
@inproceedings{GavLamRig15-ICLP-IC,
editor = {De Vos, Marina and
Thomas Eiter and
Yuliya Lierler and
Francesca Toni},
title = {An abductive Framework for {Datalog+-} Ontologies},
author = {Marco Gavanelli and Evelina Lamma and Fabrizio Riguzzi and Elena Bellodi and Riccardo Zese and Giuseppe Cota},
booktitle = {Technical Communications of the 31st Int'l.
Conference on Logic Programming (ICLP 2015)},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
address = {Aachen, Germany},
copyright = {by the authors},
year = {2015},
keywords = {Probabilistic Logic Programming, Lifted Inference,
Variable Elimination, Distribution Semantics, ProbLog,
Statistical Relational Artificial Intelligence},
abstract = {
Ontologies are a fundamental component of the Semantic Web since they provide a formal and machine manipulable model of a domain.
Description Logics (DLs) are often the languages of choice for modeling ontologies. Great effort has been spent in identifying decidable or even tractable fragments of DLs. Conversely, for knowledge representation and reasoning, integration with rules and rule-based reasoning is crucial in the so-called Semantic Web stack vision.
Datalog+- is an extension of Datalog which can be used for representing lightweight ontologies, and is able to express
the DL-Lite family of ontology languages, with tractable query answering under certain language restrictions.
In this work, we show that Abductive Logic Programming (ALP) is also a suitable framework for representing Datalog+- ontologies, supporting query answering through an abductive proof procedure, and smoothly achieving the integration of ontologies and rule-based reasoning.
In particular, we consider an Abductive Logic Programming framework named
SCIFF, and derived from the IFF abductive framework, able to deal with existentially (and universally) quantified variables in rule heads, and Constraint Logic Programming constraints.
Forward and backward reasoning is naturally supported in the ALP framework. We show that the SCIFF language smoothly supports the integration of rules, expressed in a Logic Programming language, with Datalog+- ontologies, mapped into SCIFF (forward) integrity constraints.
},
keywords = {Abductive Logic Programming, Datalog+-,
Description Logics,
Semantic Web.},
number = {1433},
url = {http://ceur-ws.org/Vol-1433/tc_89.pdf}
}
@inproceedings{GavLamRig15-CILC15-NC,
title = {Abductive Logic Programming for {Datalog+-} Ontologies},
author = {Marco Gavanelli and Evelina Lamma and Fabrizio Riguzzi and Elena Bellodi and Riccardo Zese and Giuseppe Cota},
booktitle = {Proceedings of the 30th Italian Conference on Computational Logic ({CILC2015}),
Genova, Italy, 1-3 July 2015},
editor = {Davide Ancona and
Marco Maratea and
Viviana Mascardi},
year = {2015},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
address = {Aachen, Germany},
copyright = {by the authors},
abstract = {
Ontologies are a fundamental component of the Semantic Web since they provide a formal and machine manipulable model of a domain.
Description Logics (DLs) are often the languages of choice for modeling ontologies. Great effort has been spent in identifying decidable or even tractable fragments of DLs. Conversely, for knowledge representation and reasoning, integration with rules and rule-based reasoning is crucial in the so-called Semantic Web stack vision.
Datalog+- is an extension of Datalog which can be used for representing lightweight ontologies, and is able to express
the DL-Lite family of ontology languages, with tractable query answering under certain language restrictions.
In this work, we show that Abductive Logic Programming (ALP) is also a suitable framework for representing Datalog+- ontologies, supporting query answering through an abductive proof procedure, and smoothly achieving the integration of ontologies and rule-based reasoning.
In particular, we consider an Abductive Logic Programming framework named SCIFF, and derived from the IFF abductive framework, able to deal with existentially (and universally) quantified variables in rule heads, and Constraint Logic Programming constraints.
Forward and backward reasoning is naturally supported in the ALP framework.
The SCIFF language smoothly supports the integration of rules, expressed in a Logic Programming language, with Datalog+- ontologies, mapped into SCIFF (forward) integrity constraints.
The main advantage is that this integration is achieved within a single language, grounded on abduction in computational logic.
},
keywords = { Abductive Logic Programming, Description Logics, Semantic Web},
number = {1459},
pages = {128-143},
url = {http://ceur-ws.org/Vol-1459/paper21.pdf}
}
This file was generated by bibtex2html 1.98.