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Improving strategic decision making by the detection of weak signals in heterogeneous documents by text mining techniques

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Improving strategic decision making by the detection of weak signals in heterogeneous documents by text mining techniques

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Nombre: Griol;Milla;Millet ...
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dc.contributor.author Griol Barres, Israel es_ES
dc.contributor.author Milla, Sergio es_ES
dc.contributor.author Millet Roig, José es_ES
dc.date.accessioned 2020-07-07T03:32:35Z
dc.date.available 2020-07-07T03:32:35Z
dc.date.issued 2019 es_ES
dc.identifier.issn 0921-7126 es_ES
dc.identifier.uri http://hdl.handle.net/10251/147520
dc.description.abstract [EN] At present, one of the greatest threats to companies is not being able to cope with the constant changes that occur in the market because they do not predict them well in advance. Therefore, the development of new processes that facilitate the detection of significant phenomena and future changes is a key component for correct decision making that sets a correct course in the company. For this reason, a business intelligence architecture system is hereby proposed to allow the detection of discrete changes or weak signals in the present, indicative of more significant phenomena and transcendental changes in the future. In contrast to work currently available focusing on structured information sources, or at most with a single type of data source, the detection of these signals is here quantitatively based on heterogeneous and unstructured documents of various kinds (scientific journals, newspaper articles and social networks), to which text mining and natural language processing techniques (a multi-word expression analysis) are applied. The system has been tested to study the future of the artificial intelligence sector, obtaining promising results to help business experts in the recognition of new driving factors of their markets and the development of new opportunities. es_ES
dc.description.sponsorship This work is partially supported by EIT Climate KIC of the European Union (project Accelerator TC2018B-2.2.5-ACCUPV-P066-1A) and Erasmus+ InnoCENS (573965-EPP-1-2016-1-SE-EPPKA2-CBHE-JP). es_ES
dc.language Inglés es_ES
dc.publisher IOS Press es_ES
dc.relation.ispartof AI Communications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Weak signal of the future es_ES
dc.subject Strategic decision making es_ES
dc.subject Text mining es_ES
dc.subject Business intelligence architecture es_ES
dc.subject Unstructured information es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Improving strategic decision making by the detection of weak signals in heterogeneous documents by text mining techniques es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3233/AIC-190625 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EIT Climate-KIC//TC2018B-2.2.5-ACCUPV-P066-1A/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/Erasmus+/573965-EPP-1-2016-1-SE-EPPKA2-CBHE-JP/EU/Enhancing innovation competences and entrepreneurial skills in engineering education/InnoCENS/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Griol Barres, I.; Milla, S.; Millet Roig, J. (2019). Improving strategic decision making by the detection of weak signals in heterogeneous documents by text mining techniques. AI Communications. 32(5-6):347-360. https://doi.org/10.3233/AIC-190625 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3233/AIC-190625 es_ES
dc.description.upvformatpinicio 347 es_ES
dc.description.upvformatpfin 360 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 32 es_ES
dc.description.issue 5-6 es_ES
dc.relation.pasarela S\397429 es_ES
dc.contributor.funder EIT Climate-KIC es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Erasmus+ es_ES
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dc.subject.ods 08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos es_ES


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