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Leveraging temporal expressions for segmented-based information retrieval

datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg07:Energias Renováveis e Acessíveis
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorCraveiro, Olga
dc.contributor.authorMacedo, Joaquim
dc.contributor.authorMadeira, Henrique
dc.date.accessioned2025-12-02T15:13:50Z
dc.date.available2025-12-02T15:13:50Z
dc.date.issued2010-11
dc.descriptionEISBN - 978-1-4244-8136-1
dc.descriptionConference date - 29 November 2010 - 1 December 2010; Conference code - 83753
dc.description.abstractThe extraction of temporal information from text documents is becoming increasingly important in many applications such as natural language processing, information retrieval, question answering, etc. Indeed, the temporal dimension plays a key role on most of these systems, promoting better performance. Our goal is the definition of a temporal document representation, incorporating the time dimension into information retrieval model to improve the quality of the results. Our approach is based on temporal segmentation of documents. Temporal-aware retrieval models may explore a richer temporal document representation, enabled by segmentation. To achieve this, first we must identify temporal expressions and capture, when possible, their normalized time values. Starting from our prior work on temporal expressions recognition, we present in this paper, a resolution tool that achieves promising results in a Portuguese collection. Furthermore, a temporal characterization of the used collection shows enough and suitable information for a meaningful temporal document segmentation.eng
dc.description.sponsorshipThis work is partially sponsored by Fundação para a Ciência e a Tecnologia (FCT), under the grant SFRH/BD/48583/2008.
dc.identifier.citationO. Craveiro, J. Macedo and H. Madeira, "Leveraging temporal expressions for segmented-based information retrieval," 2010 10th International Conference on Intelligent Systems Design and Applications, Cairo, Egypt, 2010, pp. 754-759, doi: https://doi.org/10.1109/ISDA.2010.5687172.
dc.identifier.doi10.1109/isda.2010.5687172
dc.identifier.eissn2164-7151
dc.identifier.isbn978-1-4244-8134-7
dc.identifier.isbn978-1-4244-8136-1
dc.identifier.issn2164-7143
dc.identifier.urihttp://hdl.handle.net/10400.8/14809
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/5687172
dc.relation.ispartof2010 10th International Conference on Intelligent Systems Design and Applications
dc.rights.uriN/A
dc.subjectData mining
dc.subjectCalendars
dc.subjectClocks
dc.subjectInformation retrieval
dc.subjectIntelligent systems
dc.subjectTraining
dc.subjectFrequency measurement
dc.titleLeveraging temporal expressions for segmented-based information retrievaleng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2010-11
oaire.citation.conferencePlaceCairo, Egypt
oaire.citation.endPage759
oaire.citation.startPage754
oaire.citation.titleProceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10International Conference on Intelligent Systems Design and Applications
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameCraveiro
person.givenNameOlga
person.identifier.orcid0000-0001-5307-0465
relation.isAuthorOfPublicationd116d598-4bbf-4608-b721-7500260b918f
relation.isAuthorOfPublication.latestForDiscoveryd116d598-4bbf-4608-b721-7500260b918f

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The extraction of temporal information from text documents is becoming increasingly important in many applications such as natural language processing, information retrieval, question answering, etc. Indeed, the temporal dimension plays a key role on most of these systems, promoting better performance. Our goal is the definition of a temporal document representation, incorporating the time dimension into information retrieval model to improve the quality of the results. Our approach is based on temporal segmentation of documents. Temporal-aware retrieval models may explore a richer temporal document representation, enabled by segmentation. To achieve this, first we must identify temporal expressions and capture, when possible, their normalized time values. Starting from our prior work on temporal expressions recognition, we present in this paper, a resolution tool that achieves promising results in a Portuguese collection. Furthermore, a temporal characterization of the used collection shows enough and suitable information for a meaningful temporal document segmentation.
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