Probabilistic reasoning is an essential feature when dealing with many application domains. Starting with the idea that ontologies are the right way to formalize domain knowledge and that Bayesian networks are the right tool for probabilistic reasoning, we propose an approach for extracting a Bayesian network from a populated ontology and for reasoning over it. The paper presents the theory behind the approach, its design and examples of its use
Mining Bayesian networks out of ontologies
Bellandi A;Turini F
2012
Abstract
Probabilistic reasoning is an essential feature when dealing with many application domains. Starting with the idea that ontologies are the right way to formalize domain knowledge and that Bayesian networks are the right tool for probabilistic reasoning, we propose an approach for extracting a Bayesian network from a populated ontology and for reasoning over it. The paper presents the theory behind the approach, its design and examples of its use| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.ancejournal | JOURNAL OF INTELLIGENT INFORMATION SYSTEMS | - |
| dc.authority.orgunit | Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI | - |
| dc.authority.people | Bellandi A | it |
| dc.authority.people | Turini F | it |
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| dc.collection.name | 01.01 Articolo in rivista | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
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| dc.date.accessioned | 2024/02/16 04:58:32 | - |
| dc.date.available | 2024/02/16 04:58:32 | - |
| dc.date.issued | 2012 | - |
| dc.description.abstracteng | Probabilistic reasoning is an essential feature when dealing with many application domains. Starting with the idea that ontologies are the right way to formalize domain knowledge and that Bayesian networks are the right tool for probabilistic reasoning, we propose an approach for extracting a Bayesian network from a populated ontology and for reasoning over it. The paper presents the theory behind the approach, its design and examples of its use | - |
| dc.description.affiliations | Port Authority of Livorno, Livorno, Italy; Department of Computer Science, University of Pisa, Pisa, Italy - CNR-ISTI, Pisa, Italy | - |
| dc.description.allpeople | Bellandi, A; Turini, F | - |
| dc.description.allpeopleoriginal | Bellandi A.; Turini F. | - |
| dc.description.fulltext | restricted | en |
| dc.description.note | Progetto: Financial Risk Management Ontology of the UE Projec Acronimo: musing 2006 Tipo Progetto: EU | - |
| dc.description.numberofauthors | 2 | - |
| dc.identifier.doi | 10.1007/s10844-011-0165-4 | - |
| dc.identifier.isi | WOS:000302240800009 | - |
| dc.identifier.scopus | 2-s2.0-84862193882 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/6121 | - |
| dc.identifier.url | http://link.springer.com/article/10.1007%2Fs10844-011-0165-4 | - |
| dc.language.iso | eng | - |
| dc.relation.firstpage | 507 | - |
| dc.relation.issue | 2 | - |
| dc.relation.lastpage | 532 | - |
| dc.relation.volume | 38 | - |
| dc.subject.keywords | Probabilistic reasoning | - |
| dc.subject.keywords | Ontology queries | - |
| dc.subject.singlekeyword | Probabilistic reasoning | * |
| dc.subject.singlekeyword | Ontology queries | * |
| dc.title | Mining Bayesian networks out of ontologies | en |
| dc.type.driver | info:eu-repo/semantics/article | - |
| dc.type.full | 01 Contributo su Rivista::01.01 Articolo in rivista | it |
| dc.type.miur | 262 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
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| iris.isi.extIssued | 2012 | - |
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| isi.contributor.affiliation | Livorno Port Author | - |
| isi.contributor.affiliation | University of Pisa | - |
| isi.contributor.country | Italy | - |
| isi.contributor.country | Italy | - |
| isi.contributor.name | Bellandi | - |
| isi.contributor.name | Turini | - |
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| isi.contributor.subaffiliation | Dept Comp Sci | - |
| isi.contributor.surname | Andrea | - |
| isi.contributor.surname | Franco | - |
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| isi.description.abstracteng | Probabilistic reasoning is an essential feature when dealing with many application domains. Starting with the idea that ontologies are the right way to formalize domain knowledge and that Bayesian networks are the right tool for probabilistic reasoning, we propose an approach for extracting a Bayesian network from a populated ontology and for reasoning over it. The paper presents the theory behind the approach, its design and examples of its use. | * |
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| isi.journal.journaltitleabbrev | J INTELL INF SYST | * |
| isi.language.original | English | * |
| isi.publisher.place | VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS | * |
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| scopus.contributor.name | Bellandi | - |
| scopus.contributor.name | Turini | - |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | Department of Computer Science; | - |
| scopus.contributor.surname | Andrea | - |
| scopus.contributor.surname | Franco | - |
| scopus.date.issued | 2012 | * |
| scopus.description.abstracteng | Probabilistic reasoning is an essential feature when dealing with many application domains. Starting with the idea that ontologies are the right way to formalize domain knowledge and that Bayesian networks are the right tool for probabilistic reasoning, we propose an approach for extracting a Bayesian network from a populated ontology and for reasoning over it. The paper presents the theory behind the approach, its design and examples of its use. © Springer Science+Business Media, LLC 2011. | * |
| scopus.description.allpeopleoriginal | Andrea B.; Franco T. | * |
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| scopus.subject.keywords | Ontology queries; Probabilistic reasoning; | * |
| scopus.title | Mining Bayesian networks out of ontologies | * |
| scopus.titleeng | Mining Bayesian networks out of ontologies | * |
| Appare nelle tipologie: | 01.01 Articolo in rivista | |
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