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ETLAnow: A Model for Forecasting with Big Data

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ETLAnow: A Model for Forecasting with Big Data

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dc.contributor.author Tuhkuri, Joonas es_ES
dc.date.accessioned 2018-01-29T08:12:03Z
dc.date.available 2018-01-29T08:12:03Z
dc.date.issued 2016-10-10
dc.identifier.isbn 9788490484623
dc.identifier.uri http://hdl.handle.net/10251/95626
dc.description Abstract de la ponencia es_ES
dc.description.abstract [EN] In this paper we document the ETLAnow project. ETLAnow is a model for forecasting with big data. At the moment, it predicts the unemployment rate in the EU-28 countries using Google search data. The model is publicly available at the ETLAnow’s website, http://www.etlanow.eu. The forecast model is based on the idea that volumes of Google searches could be associated with the current and future level of an economic index. And these data are available earlier than official statistics. The motivation for our approach is that big data could help produce more accurate economic forecasts. Those forecasts would inform better policy and decisions, and help real people—especially during an economic crisis. es_ES
dc.format.extent 1 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject web data es_ES
dc.subject internet data es_ES
dc.subject big data es_ES
dc.subject qca es_ES
dc.subject pls es_ES
dc.subject sem es_ES
dc.subject conference es_ES
dc.title ETLAnow: A Model for Forecasting with Big Data es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2016.2015.4224
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Tuhkuri, J. (2016). ETLAnow: A Model for Forecasting with Big Data. En CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics. Editorial Universitat Politècnica de València. 116-116. https://doi.org/10.4995/CARMA2016.2015.4224 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate July 06-07,2016 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2016/paper/view/4224 es_ES
dc.description.upvformatpinicio 116 es_ES
dc.description.upvformatpfin 116 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\4224 es_ES


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