@inproceedings{GraLamMel97-NW,
author = {Fausto Gramantieri and Evelina Lamma and Paola Mello and Fabrizio Riguzzi},
title = {Un Sistema Basato sulla Conoscenza per il Calcolo dei Function Point},
booktitle = {Incontro del Gruppo di Lavoro su Rapprensentazione della Conoscenza e
Ragionamento Automatico dell'Associazione Italiana per l'Intelligenza Artificiale (AI*IA)
e dell'Associazione italiana Tecnologie Avanzate Basate su concetti Orientati ad Oggetti
(TABOO) dal titolo ``Rappresentazione della conoscenza e
tecniche ad oggetti nell'ingegneria del software'', Bologna, 4 \April\ 1997},
month = apr,
year = 1997,
pdf = {http://ml.unife.it/wp-content/uploads/Papers/GraLamMel-TABOO97.pdf}
}
@inproceedings{MilOmiRig97-NW,
author = {Michela Milano and Andrea Omicini and Fabrizio Riguzzi},
title = {Learning with an Object-Oriented Data Model},
booktitle = {Incontro dei Gruppi di Lavoro su Apprendimento Automatico e
Linguaggio Naturale dell'Associazione
Italiana per l'Intelligenza Artificiale (AIIA)},
month = dec,
year = 1997,
pdf = {http://ml.unife.it/wp-content/uploads/Papers/MilOmiRig-AALN97.pdf}
}
@inproceedings{Rig05-RCRA05-NW,
author = {Fabrizio Riguzzi},
title = {A Comparison of {ILP} Systems on the {Sisyphus} Dataset},
pdf = {http://ml.unife.it/wp-content/uploads/Papers/rcra2005cr%20riguzzi.pdf},
booktitle = {Incontro del Gruppo di Lavoro
Rappresentazione della Conoscenza e Ragionamento Automatico
({RCRA}) dell'Associazione Italiana per l'Intelligenza Artificiale ({AI*IA}) dal titolo
``Analisi Sperimentale e Benchmark di Algoritmi per l'Intelligenza Artificiale'', 10 giugno 2005},
keywords = {Machine Learning, Inductive Logic Programming},
abstract = {In this paper we present a comparison of two Inductive Logic
Programming (ILP) systems on the Sisyphus dataset. The aim of the
comparison is to to show how the systems behave on a large
dataset. The considered systems are Aleph and Tilde. Both
systems have an unacceptable execution time on the whole dataset,
so they are run over samples extracted from the dataset.
The comparison shows that, on average, Tilde finds more accurate
theories in a smaller time.
},
editor = {Marco Cadoli and Marco Gavanelli and Tony Mancini},
month = jun,
year = {2005},
address = {Ferrara, \Italy},
issn = {1724-8035}
}
@inproceedings{FlaMarRig06-RCRA06-NW,
author = {Peter Flach and Valentina Maraldi and Fabrizio Riguzzi},
title = {Algorithms for Efficiently and Effectively Using Background Knowledge in Tertius},
pdf = {http://ml.unife.it/wp-content/uploads/Papers/FlaMarRig-RCRA06.pdf},
booktitle = {Incontro del Gruppo di Lavoro
Rappresentazione della Conoscenza e Ragionamento Automatico
({RCRA}) dell'Associazione Italiana per l'Intelligenza Artificiale ({AI*IA}) dal titolo
``Analisi Sperimentale e Benchmark di Algoritmi per l'Intelligenza Artificiale'', 23 giugno 2006},
keywords = {Machine Learning, Inductive Logic Programming},
abstract = {\texttt{Tertius} is an Inductive Logic Programming system that performs
confirmatory induction, i.e., it looks for the $n$ clauses that have the
highest
value of a confirmation evaluation function. In this setting, background
knowledge is very useful because it can improve the reliability of
the evaluation function, assigning minimal confirmation to clauses that
are implied by the background knowledge and increasing the confirmation of the remaining clauses.
We propose the algorithms \emph{Background1} and \emph{Background2} that look for clauses in the background that imply
the clause under evaluation by \texttt{Tertius}. Both are based on a simplified implication test
that is correct with respect to $\theta$-subsumption but not complete.
The implication test is not complete because we want to keep the run time inside
acceptable bounds.
We compare \emph{Background1} with \emph{Background2} on two datasets. The results
show that \emph{Background2} is more efficient than \emph{Background1}.
Moreover, we also present the
algorithm \emph{Preprocess} that infers new clauses from the background knowledge in order to
exploit it as much as possible.
The algorithm modifies the
consequence finding algorithm proposed by Inoue by reducing its
execution time while giving up completeness.
},
editor = {Marco Gavanelli and Tony Mancini},
month = jun,
year = {2006},
address = {Udine, \Italy}
}
@inproceedings{LamMelRig06-RCRA06-NW,
author = {Evelina Lamma and Paola Mello and Fabrizio Riguzzi},
title = {Exploiting Abduction for Learning from Incomplete Interpretations},
pdf = {http://ml.unife.it/wp-content/uploads/Papers/LamMelRig-RCRA06.pdf},
booktitle = {Incontro del Gruppo di Lavoro
Rappresentazione della Conoscenza e Ragionamento Automatico
({RCRA}) dell'Associazione Italiana per l'Intelligenza Artificiale ({AI*IA}) dal titolo
``Analisi Sperimentale e Benchmark di Algoritmi per l'Intelligenza Artificiale'', 23 giugno 2006},
keywords = {Machine Learning, Inductive Logic Programming},
abstract = {In this paper we describe an approach for integrating abduction
and induction in the ILP setting of learning from interpretations
with the aim of solving the problem of incomplete information both
in the background knowledge and in the interpretations. The
approach is inspired by the techniques developed in the learning
from entailment setting for performing induction from an
incomplete background knowledge. Similarly to those techniques,
we exploit an abductive proof procedure for completing the
available background knowledge and input interpretations.
The approach has been implemented in a system called AICL that is
based on the ILP system ICL. Preliminary experiments have been
performed on a toy domain where knowledge has been gradually
removed. The experiments show that AICL has an accuracy
that is superior to the one of ICL for levels of incompleteness between 5\% and 25\%.
},
editor = {Marco Gavanelli and Tony Mancini},
month = jun,
year = {2006},
address = {Udine, \Italy}
}
@inproceedings{AlbGavLam09-CEUR-NW,
author = {Marco Alberti and
Marco Gavanelli and
Evelina Lamma and
Fabrizio Riguzzi and
Sergio Storari },
editor = {Matteo Baldoni and
Cristina Baroglio},
booktitle = {Il Milione (i.e. $2^6$, June 3rd 2008)
A Journey in the Computational Logic in Italy, Proceedings of the Day Dedicated to Prof. {Alberto Martelli}
Turin, Italy, June 3, 2008},
title = {Inducing Specification of Interaction Protocols and Business Processes and Proving their Properties},
year = {2009},
abstract = {In this paper, we overview our recent research
activity concerning the induction of Logic Programming
specifications, and the proof of their properties via Abductive
Logic Programming. Both the inductive and abductive tools here
briefly described have been applied to respectively learn and verify
(properties of) interaction protocols in multi-agent systems, Web
service choreographies, careflows and business processes.},
pdf = {http://ceur-ws.org/Vol-487/paper6.pdf},
series = {CEUR Workshop Proceedings},
publisher = {Sun {SITE} Central Europe},
issn = {1613-0073},
volume = {487},
pages = {32-37},
address = {Aachen, \Germany},
keywords = {Business Process Management, Logic Programming}
}
@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}
}
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