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dc.contributor.authorAnselma, Luca
dc.contributor.authorPiovesan, Luca
dc.contributor.authorTerenziani, Paolo
dc.date.accessioned2020-01-24T01:33:39Z
dc.date.available2020-01-24T01:33:39Z
dc.date.issued2019
dc.identifier.issn0921-7126
dc.identifier.doi10.3233/AIC-190619
dc.identifier.urihttp://hdl.handle.net/10072/390853
dc.description.abstractTime is pervasive of the human way of approaching reality, so that it has been widely studied in many research areas, including AI and relational Temporal Databases (TDB). While temporally imprecise information has been widely studied by the AI community, only few approaches have faced temporal indeterminacy (in particular, “don’t know exactly when” indeterminacy) in TDBs. Indeed, as we will show in this paper, the treatment of time in general, and of temporal indeterminacy in particular, involves the introduction of implicit forms of data representation in TDBs. As a consequence, we propose a new AI-style methodology to cope with temporal indeterminacy in TDBs. Specifically, we show that typical AI notions and techniques, such as making explicit the semantics of the representation formalism, and adopting symbolic manipulation techniques based on such a semantics, can be fruitfully exploited in the development of a “principled” treatment of indeterminate time in relational databases.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherIOS Press
dc.relation.ispartofpagefrom207
dc.relation.ispartofpageto221
dc.relation.ispartofissue3
dc.relation.ispartofjournalAI Communications
dc.relation.ispartofvolume32
dc.subject.fieldofresearchArtificial intelligence
dc.subject.fieldofresearchCognitive and computational psychology
dc.subject.fieldofresearchcode4602
dc.subject.fieldofresearchcode5204
dc.subject.keywordsScience & Technology
dc.subject.keywordsTechnology
dc.subject.keywordsComputer Science, Artificial Intelligence
dc.subject.keywordsComputer Science
dc.subject.keywordsTemporal data
dc.titleDealing with temporal indeterminacy in relational databases: An AI methodology
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationAnselma, L; Piovesan, L; Terenziani, P, Dealing with temporal indeterminacy in relational databases: An AI methodology, AI Communications, 2019, 32 (3), pp. 207-221
dc.date.updated2020-01-24T01:30:50Z
gro.hasfulltextNo Full Text
gro.griffith.authorTerenziani, Paolo


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