QuickSearch:   Number of matching entries: 0.

Search Settings

    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Ardissono, L., Portis, F. & Torasso, P. Architecture of a System for the Generation of Personalized Electronic Program Guides 2002 Proceedings of the 1st Workshop on Personalization in Future TV  inproceedings  
    BibTeX:
    @inproceedings{ardissonoportistorasso2001,
      author = {L. Ardissono and F. Portis and P. Torasso},
      title = {Architecture of a System for the Generation of Personalized Electronic Program Guides},
      booktitle = {Proceedings of the 1st Workshop on Personalization in Future TV},
      year = {2002}
    }
    
    Ardissono, L., Portis, F., Torasso, P., Bellifemine, F., Chiarotto, A. & Difino, A. Architecture of a System for the Generation of Personalized Electronic Program Guides 2001 Workshop on Personalization in Future TV, User Modeling 2001  inproceedings  
    BibTeX:
    @inproceedings{Ard01a,
      author = {L. Ardissono and F. Portis and P. Torasso and F. Bellifemine and A. Chiarotto and A. Difino},
      title = {Architecture of a System for the Generation of Personalized Electronic Program Guides},
      booktitle = {Workshop on Personalization in Future TV, User Modeling 2001},
      year = {2001}
    }
    
    Cohen, W.W. & Hirsh, H. Learning the Classic Description Logic: Theoretical and Experimental Results 1994 Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, pp. 121-133  inproceedings  
    BibTeX:
    @inproceedings{kr94*121,
      author = {William W. Cohen and Haym Hirsh},
      title = {Learning the Classic Description Logic: Theoretical and Experimental Results},
      booktitle = {Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning},
      publisher = {Morgan Kaufmann},
      year = {1994},
      pages = {121--133}
    }
    
    Guarino, N., Carrara, M. & Giaretta, P. An Ontology of Meta-Level Categories 1994 KR'94: Principles of Knowledge Representation and Reasoning, pp. 270-280  incollection URL 
    BibTeX:
    @incollection{guarino94ontology,
      author = {Nicola Guarino and Massimiliano Carrara and Pierdaniele Giaretta},
      title = {An Ontology of Meta-Level Categories},
      booktitle = {KR'94: Principles of Knowledge Representation and Reasoning},
      publisher = {Morgan Kaufmann},
      year = {1994},
      pages = {270--280},
      url = {citeseer.ist.psu.edu/article/guarino94ontology.html}
    }
    
    Portinale, L. & Torasso, P. Case-Base Maintenance in a Multimodal Reasoning System 2001 Computational Intelligence
    Vol. 17(2), pp. 263-279 
    article  
    Abstract: The definition of suitable case-base maintenance policies is widely recognized as a major key to success for case-based systems; underestimating this issue may lead to systems that either do not fulfill their role of knowledge management and preservation or that do not perform adequately under performance dimensions, namely, computation time and competence and quality of solutions. The goal of this article is to analyze some automatic case-base management strategies in the context of a multimodal architecture combining case-based reasoning and model-based reasoning. We propose and compare two different methodologies, the first one, called replace, is a competence-based strategy aimed at replacing a set of stored cases with the current one, if the latter exhibits an estimated competence comparable with the estimated competence of the considered set of stored cases. The second one, called learning by failure with forgetting (LFF), is based on incremental learning of cases interleaved with off-line processes of forgetting (deleting) cases whose usage does not fulfill specific utility conditions. Results from an extensive experimental analysis in an industrial plant diagnosis domain are reported, showing the usefulness of both strategies with respect to the maintenance of suitable performance levels for the target system.
    BibTeX:
    @article{PortinaleTorasso01,
      author = {Luigi Portinale and Pietro Torasso},
      title = {Case-Base Maintenance in a Multimodal Reasoning System},
      journal = {Computational Intelligence},
      year = {2001},
      volume = {17},
      number = {2},
      pages = {263--279}
    }
    
    Portinale, L. & Torasso, P. Automatic Case Base Management in a Multi-Modal Reasoning System 2000 Advances in Case-Based Reasoning, Proceedings of the 5th European Workshop on Case-Based Reasoning, EWCBR 2000, Trento, Italy, pp. 234-246  inproceedings  
    Abstract: The definition of suitable case base maintenance policies is widely recognized as a major success key of CBR systems; underestimating this issue may lead to systems that do not perform adequately under performance dimensions, namely computation time, competence, and quality of solutions. The goal of the present paper is to analyze an automatic case base management strategy in the context of multi-modal architectures combining CBR and Model-Based Reasoning. The strategy, called Learning by Failure with Forgetting (LFF) is based on incremental learning of cases interleaved with off-line processes of case deletion, in order to control the content and the size of the case library. Results from an extensive experimental analysis in an industrial plant diagnosis domain is then reported, showing the usefulness of LFF with respect to the maintenance of suitable performance level for the target system.
    BibTeX:
    @inproceedings{PortinaleTorasso00,
      author = {Luigi Portinale and Pietro Torasso},
      title = {Automatic Case Base Management in a Multi-Modal Reasoning System},
      booktitle = {Advances in Case-Based Reasoning, Proceedings of the 5th European Workshop on Case-Based Reasoning, EWCBR 2000, Trento, Italy},
      publisher = {Springer-Verlag},
      year = {2000},
      pages = {234--246}
    }
    
    Portinale, L., Torasso, P. & Tavano, P. Speed-Up, Quality and Competence in Multi-model Case-Based Reasoning 2000 Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, pp. 234-246  inproceedings  
    BibTeX:
    @inproceedings{PortinaleEtAl00,
      author = {L. Portinale and P. Torasso and P. Tavano},
      title = {Speed-Up, Quality and Competence in Multi-model Case-Based Reasoning},
      booktitle = {Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence},
      publisher = {Springer Verlag },
      year = {2000},
      pages = {234-246}
    }
    
    Portinale, L., Torasso, P. & Tavano, P. Speed-Up, Quality and Competence in Multi-model Case-Based Reasoning 1999 Case-Based Reasoning Reasearch and Developments. Lecture Notes in Artificial Intelligence, pp. 303-317  inproceedings  
    BibTeX:
    @inproceedings{PortinaleEtAl99,
      author = {L. Portinale and P. Torasso and P. Tavano},
      title = {Speed-Up, Quality and Competence in Multi-model Case-Based Reasoning},
      booktitle = {Case-Based Reasoning Reasearch and Developments. Lecture Notes in Artificial Intelligence},
      publisher = {Springer Verlag },
      year = {1999},
      pages = {303-317}
    }
    
    Portinale, L., Torasso, P. & Tavano, P. Speed-Up, Quality and Competence in Multi-Modal Case-Based Reasoning 1999 Case-Based Reasoning Research and Development: Proceedings of the Third International Conference on Case-Based Reasoning, ICCBR'99, Seeon Monastery, Germany, pp. 303-317  inproceedings  
    Abstract: The paper discusses the different aspects concerning performance arising in multi-modal systems combining Case-Based Reasoning and Model-Based Reasoning for diagnostic problem solving. In particular, we examine the relation among speed-up of problems solving, competence of the system and quality of produced solutions. Because of the well-known utility problem, there is no general strategy for improving all theses parameters at the same time, so the trade-off among such parameters must be carefully analyzed. We have developed a case memory management strategy which allows the interleaving of learning of new cases with forgetting phases, where useless and potentially dangerous cases are identified and removed. This strategy, combined with a suitable tuning on the precision required for the retrieval of cases (in terms of estimated adaptation cost), provides an effective mechanism for taking under control the utility problem. Experimental analysis performed on a real-world domain shows in fact that improvements over both speed-up and competence can be obtained, without compromising in a significant way the quality of solutions.
    BibTeX:
    @inproceedings{PortinaleTorassoTavano99,
      author = {Luigi Portinale and Pietro Torasso and Paolo Tavano},
      title = {Speed-Up, Quality and Competence in Multi-Modal Case-Based Reasoning},
      booktitle = {Case-Based Reasoning Research and Development: Proceedings of the Third International Conference on Case-Based Reasoning, ICCBR'99, Seeon Monastery, Germany},
      publisher = {Springer-Verlag},
      year = {1999},
      pages = {303--317}
    }
    
    Portinale, L., Torasso, P. & Tavano, P. Dynamic Case Memory Management 1998 Proceedings of the European Conference on Artificial Intelligence, pp. 73-78  inproceedings  
    BibTeX:
    @inproceedings{PortinaleEtAl98,
      author = {L. Portinale and P. Torasso and P. Tavano},
      title = {Dynamic Case Memory Management},
      booktitle = {Proceedings of the European Conference on Artificial Intelligence},
      year = {1998},
      pages = {73-78}
    }
    

    Created by JabRef on 30/08/2008.