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Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing

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Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing

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dc.contributor.author Griol-Barres, Israel es_ES
dc.contributor.author Milla, Sergio es_ES
dc.contributor.author Cebrián Ferriols, Antonio José es_ES
dc.contributor.author Fan, Huaan es_ES
dc.contributor.author Millet Roig, José es_ES
dc.date.accessioned 2021-05-22T03:32:05Z
dc.date.available 2021-05-22T03:32:05Z
dc.date.issued 2020-10 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166654
dc.description.abstract [EN] Organizations, companies and start-ups need to cope with constant changes on the market which are difficult to predict. Therefore, the development of new systems to detect significant future changes is vital to make correct decisions in an organization and to discover new opportunities. A system based on business intelligence techniques is proposed to detect weak signals, that are related to future transcendental changes. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic and social sources, applying text mining to analyze the documents and natural language processing to extract accurate results. The main contributions are that the system has been designed for any field, using different input datasets of documents, and with an automatic classification of categories for the detected keywords. In this research paper, results from the future of remote sensors are presented. Remote sensing services are providing new applications in observation and analysis of information remotely. This market is projected to witness a significant growth due to the increasing demand for services in commercial and defense industries. The system has obtained promising results, evaluated with two different methodologies, to help experts in the decision-making process and to discover new trends and opportunities. es_ES
dc.description.sponsorship This research is partially supported by EIT Climate-KIC of the European Institute of Technology (project EIT Climate-KIC Accelerator-TC_3.1.5_190607_P066-1A) and InnoCENS from Erasmus + (573965-EPP-1-2016-1-SE-EPPKA2-CBHE-JP). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Sustainability es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject New sustainable business models es_ES
dc.subject Business intelligence es_ES
dc.subject Natural language processing es_ES
dc.subject Weak signals of the future es_ES
dc.subject Predictive models es_ES
dc.subject Text mining es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/su12197848 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.relation.projectID info:eu-repo/grantAgreement/EIT Climate-KIC//TC_3.1.5_190607_P066-1A/ es_ES
dc.rights.accessRights Abierto 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.; Cebrián Ferriols, AJ.; Fan, H.; Millet Roig, J. (2020). Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing. Sustainability. 12(19):1-21. https://doi.org/10.3390/su12197848 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/su12197848 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 21 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 19 es_ES
dc.identifier.eissn 2071-1050 es_ES
dc.relation.pasarela S\418317 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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