author = { Riguzzi, Fabrizio},
  title = {The {SLGAD} Procedure for Inference on Logic Programs with Annotated Disjunctions},
  year = 2008,
  number = {CS-2008-01},
  institution = {Dipartimento di Ingegneria, Universit\`{a} di Ferrara},
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/cs-2008-01.pdf},
  abstract = {Logic Programs with Annotated Disjunctions (LPADs) allow
to express probabilistic information in logic programming. The semantics
of an LPAD is given in terms of well founded models of the normal logic
programs obtained by selecting one disjunct from each ground LPAD
clause. The paper presents SLGAD resolution that computes the (con-
ditional) probability of a ground query from an LPAD and is based on
SLG resolution for normal logic programs. The performances of SLGAD
are evaluated on classical benchmarks for normal logic programs under
the well founded semantics, namely the stalemate game and the ancestor
relation. The results show that SLGAD has good scaling properties and
is able to deal with cyclic programs.},
  keywords = {Probabilistic Logic Programming, Well Founded Semantics, Logic
Programs with Annotated Disjunctions, SLG resolution}
  author = {Fabrizio Riguzzi},
  title = {Inference with Logic Programs with Annotated Disjunctions under the Well Founded Semantics},
  booktitle = {Logic Programming, 24th International Conference, ICLP 2008,
               Udine, Italy, December  9-13, 2008, Proceedings},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  year = {2008},
  note = {The original publication is available at \url{http://www.springerlink.com}},
  address = {Heidelberg, \Germany},
  volume = {5366},
  pages = {667-771},
  doi = {10.1007/978-3-540-89982-2_54},
  url = {http://link.springer.com/chapter/10.1007%2F978-3-540-89982-2_54},
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/Rig-ICLP08.pdf},
  copyright = {Springer}
  author = {
Federico Chesani and Paola Mello and Marco Montali and Fabrizio
Riguzzi and  Maurizio
Sebastianis and Sergio Storari},
  title = {Compliance Checking of Execution Traces to Business Rules:
an Approach based on Logic Programming},
  booktitle = {Atti del 23esimo Convegno Italiano
di Logica Computazionale, Perugia, Italia, 10-12 luglio 2008},
  year = {2008},
  abstract = {
Complex and flexible business processes are critical not only
because they are difficult to handle, but also because they often
tend to be less intelligible. Monitoring and verifying complex and
flexible processes becomes therefore a fundamental requirement. We
propose a framework for performing compliance checking of process
execution traces w.r.t.~expressive reactive business rules, tailored
to the MXML meta-model. Rules are mapped to (extensions of) Logic
Programming, to the aim of providing both monitoring and
a-posteriori verification capabilities. We show how different rule
templates, inspired by the ConDec language, can be easily specified
and then customized in the context of a real industrial case study.
We finally describe how the proposed language and its underlying
a-posteriori reasoning technique have been concretely implemented as
a ProM analysis plug-in.},
  editor = {Andrea Formisano},
  publisher = {Dipartimento di Matematica e Informatica, Universit\`a di Perugia},
  keywords = {Business Process Management, Logic Programming},
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/CheMelMon08-CILC.pdf}
  author = {
 Fabrizio Riguzzi},
  title = {{ALLPAD}: Approximate Learning of Logic Programs with Annotated Disjunctions},
  journal = {Machine Learning},
  note = {The original publication is available at \url{http://www.springerlink.com}},
  year = {2008},
  volume = {70},
  number = {2-3},
  month = mar,
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/Rig-ML07.pdf},
  doi = {10.1007/s10994-007-5032-8 },
  abstract = {Logic Programs with Annotated Disjunctions (LPADs) provide a simple 
and elegant framework for representing probabilistic knowledge in logic programming. 
In this paper we consider the problem of learning ground LPADs starting from a set of 
interpretations annotated with their probability. We present the system ALLPAD for 
solving this problem. ALLPAD modifies the previous system LLPAD in order to tackle 
real world learning problems more effectively. This is achieved by looking for an 
approximate solution rather than a perfect one. A number of experiments have been 
performed on real and artificial data for evaluating ALLPAD, showing the feasibility 
of the approach},
  keywords = {Inductive logic programming, Probabilistic logic programming, Statistical relational learning,
 Logic programs with annotated disjunctions},
  pages = {207--223},
  publisher = {Springer},
  address = {Heidelberg, \Germany},
  copyright = {Springer}
  author = {
 Evelina Lamma and Paola Mello and Fabrizio Riguzzi and Sergio Storari},
  title = {Applying Inductive Logic Programming to Process  Mining},
  booktitle = {Proceedings of the 17th International Conference on Inductive Logic Programming},
  year = {2008},
  publisher = {Springer},
  abstract = {The management of business processes has recently received a lot of attention. One of the most interesting problems is the description of a process model in a language that allows the checking of the compliance of a process execution (or trace) to the model. In this paper we propose a language  for the representation of process models that is inspired to the SCIFF language and is an extension of clausal logic. 
A process model is represented in the language as a set of integrity constraints that allow conjunctive formulas as disjuncts in the head.
We present an approach for inducing these models from data: we define a subsumption relation for the integrity constraints, we define a refinement operator and we adapt the algorithm ICL to the problem of learning such formulas. The system has been applied to the problem of inducing the model of a sealed bid auction and of the NetBill protocol. The data used for learning and testing were randomly generated from correct models of the processes.},
  keywords = {Process Mining, Learning from Interpretations, Business Processes, Interaction Protocols},
  series = {Lecture Notes in Artificial Intelligence},
  volume = {4894},
  note = {The original publication is available at \url{http://www.springerlink.com}},
  pages = {132--146},
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/LamMelRigSto-ILP07.pdf},
  doi = {10.1007/978-3-540-78469-2_16},
  url = {http://link.springer.com/chapter/10.1007%2F978-3-540-78469-2_16},
  address = {Heidelberg, \Germany},
  copyright = {Springer}

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