Turning text into research networks: information retrieval and computational ontologies in the creation of scientific Databases

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dc.contributor.authorCeci, Flavio
dc.contributor.authorPietrobon, Ricardo
dc.contributor.authorGonçalves, Alexandre
dc.coverage.spatialSan Franciscopt_BR
dc.date.accessioned2017-08-10T13:09:39Z
dc.date.accessioned2020-11-26T17:37:56Z
dc.date.available2017-08-10T13:09:39Z
dc.date.available2020-11-26T17:37:56Z
dc.date.issued2012
dc.description.abstractBackground: Web-based, free-text documents on science and technology have been increasing growing on the web. However, most of these documents are not immediately processable by computers slowing down the acquisition of useful information. Computational ontologies might represent a possible solution by enabling semantically machine readable data sets. But, the process of ontology creation, instantiation and maintenance is still based on manual methodologies and thus time and cost intensive. Method: We focused on a large corpus containing information on researchers, research fields, and institutions. We ased our strategy on traditional entity recognition, social computing and correlation. We devised a semi automatic approach for the recognition, correlation and extraction of named entities and relations from textual documents which are then used to create, instantiate, and maintain an ontology. Results: We present a prototype demonstrating the applicability of the proposed strategy, along with a case study describing how direct and indirect relations can be extracted from academic and professional activities registered in a database of curriculum vitae in free-text format. We present evidence that this system can identify entities to assist in the process of knowledge extraction and representation to support ontology maintenance. We also demonstrate the extraction of relationships among ontology classes and their instances. Conclusion: We have demonstrated that our system can be used for the conversion of research information in free text format into database with a semantic structure. Future studies should test this system using the growing number of freetext information available at the institutional and national levels.pt_BR
dc.format.extentp.1-9pt_BR
dc.identifierJaneiropt_BR
dc.identifier.issn1932-6203pt_BR
dc.identifier.other1pt_BR
dc.identifier.urihttps://repositorio.animaeducacao.com.br/handle/ANIMA/2649
dc.language.isoen_USpt_BR
dc.relation.ispartofseries7pt_BR
dc.rightsAttribution-NoDerivs 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/br/*
dc.subjectOntology maintenancept_BR
dc.subjectNamed entity recognitionpt_BR
dc.subjectKnowledge engineeringpt_BR
dc.subject.otherCiência da Computaçãopt_BR
dc.titleTurning text into research networks: information retrieval and computational ontologies in the creation of scientific Databasespt_BR
dc.typeArtigo de Periodicopt_BR
local.affiliation.iesUnisul
local.author.cursoProdução Científicapt_BR
local.author.unidadeÂnimapt_BR
local.rights.policyAcesso abertopt_BR
local.subject.areaCiências Exatas e da Terrapt_BR
local.subject.areaanimaCiências Humanaspt_BR

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