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dc.contributor.authorVARGAS, R. N. P.pt_BR
dc.contributor.authorMOURA, M. F.pt_BR
dc.contributor.authorSPERANZA, E. A.pt_BR
dc.contributor.authorRODRIGUEZ, E.pt_BR
dc.contributor.authorREZENDE, S. O.pt_BR
dc.date.accessioned2013-02-06T23:03:12Z-
dc.date.available2013-02-06T23:03:12Z-
dc.date.created2013-02-06pt_BR
dc.date.issued2012pt_BR
dc.identifier.citationIn: GEOSPATIAL INFORMATION AND DOCUMENTS; PACIFIC-ASIA CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 16., 2012, Kuala Lumpur. Workshop... [S.l.: s.n.], 2012.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/948462pt_BR
dc.descriptionAbstract. Nowadays it is becoming more usual for users to take into account the geographical localization of the documents in the retrieval information process. However, the conventional retrieval information systems based on key-word matching do not consider which words can represent geographical entities that are spatially related to other entities in the document. This paper presents the SpatialCIM methodology, which is based on three steps: pre-processing, data expansion and disambiguation. In the pre-processing step, the entity recognition process is carried out with the support of the Rembrandt tool. Additionally, a comparison between the performances regarding the discovery of the location entities in the texts of the Rembrandt tool against the use of a controlled vocabulary corresponding to the Brazilian geographic locations are presented. For the comparison a set of geographic labeled news covering the sugar cane culture in the Portuguese language is used. The results showed a F-measure value increase for the Rembrandt tool from 45% in the non-disambiguated process to 0.50 after disambiguation and from 35% to 38% using the controlled vocabulary. Additionally, the results showed the Rembrandt tool has a minimal amplitude difference between precision and recall, although the controlled vocabulary has always the biggest recall values.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectProblema de ambiguidadept_BR
dc.subjectMetodologia SpatialCIMpt_BR
dc.subjectAmbiguity Problempt_BR
dc.subjectNamed Entity Recognition and Classificationpt_BR
dc.subjectToponym resolutionpt_BR
dc.titleThe SpatialCIM methodology for spatial document coverage disambiguation and the entity recognition process aided by linguistic techniques.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2020-01-22T11:11:11Zpt_BR
dc.description.notesGeoDoc 2012, PAKDD 2012.pt_BR
dc.format.extent2Não paginado.pt_BR
riaa.ainfo.id948462pt_BR
riaa.ainfo.lastupdate2020-01-22 -02:00:00pt_BR
dc.contributor.institutionROSA NATHALIE PORTUGAL VARGAS, ICMC/USP; MARIA FERNANDA MOURA, CNPTIA; EDUARDO ANTONIO SPERANZA, CNPTIA; ERCILIA RODRIGUEZ; SOLANGE OLIVEIRA REZENDE, ICMC/USP.pt_BR
Aparece en las colecciones:Artigo em anais de congresso (CNPTIA)

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