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A Scalable Framework to Predict Bitcoin Price Using Support Vector Machine

2022Conference object Restricted access
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dc.contributor.authorMonteiro, Stéphane
dc.contributor.authorOliveira, Diogo
dc.contributor.authorAntónio, João
dc.contributor.authorHenriques, João
dc.contributor.authorMartins, Pedro
dc.contributor.authorWanzeller, Cristina
dc.contributor.authorCaldeira, Filipe
dc.date.accessioned2023-07-04T09:21:08Z
dc.date.available2023-07-04T09:21:08Z
dc.date.issued2022
dc.date.updated2023-06-09T13:35:11Z
dc.description.abstractStock analysts have been predicting other stocks prices in financial markets by understanding their patterns. Bitcoin is an example of cryptocurrency that has grow enormously since 2020 despite being in the market since 2009. However, cryptocurrencies are volatile and sensitive to thousands of factors and consequently is complex for humans to make predictions even more when those predictions should occur in a daily basis, requiring hence a significant effort. Due to this fact, investor profiles prefer long-term investments which can constraint their revenues. To overcome the aforementioned scenario this work proposes a scalable framework relying in Support Vector Machine (SVM) algorithm to predict the price of bitcoin by automatically collecting and cleaning the data directly from the Web to process the dataset as input for training. This framework can also leverage new business models at scale by assisting the investors aiming realize its value in short periods in a continuous fashion.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-031-14859-0_27pt_PT
dc.identifier.isbn9783031148583
dc.identifier.isbn9783031148590
dc.identifier.issn2194-5357
dc.identifier.issn2194-5365
dc.identifier.slugcv-prod-3037671
dc.identifier.urihttp://hdl.handle.net/10400.19/7841
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer International Publishingpt_PT
dc.subjectScalabilitypt_PT
dc.subjectMachine learningpt_PT
dc.subjectSupport vector machinept_PT
dc.subjectBitcoinpt_PT
dc.subjectStock price predictionpt_PT
dc.titleA Scalable Framework to Predict Bitcoin Price Using Support Vector Machinept_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage299pt_PT
oaire.citation.startPage293pt_PT
oaire.citation.titleDiTTEt 2022: New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligencept_PT
person.familyNameMonteiro
person.familyNameMenoita Henriques
person.familyNameWanzeller Guedes de Lacerda
person.familyNameCaldeira
person.givenNameStéphane
person.givenNameJoão Pedro
person.givenNameAna Cristina
person.givenNameFilipe
person.identifierhttps://scholar.google.pt/citations?user=AExQrJwAAAAJ
person.identifierlXPmBvYAAAAJ
person.identifier.ciencia-idBB15-BFE2-17AA
person.identifier.ciencia-idE81F-11C0-E77C
person.identifier.ciencia-idCB11-8109-AB1D
person.identifier.orcid0000-0003-0252-6463
person.identifier.orcid0000-0001-7380-9511
person.identifier.orcid0000-0001-7558-2330
person.identifier.scopus-author-id36023210300
rcaap.cv.cienciaidCB11-8109-AB1D | Filipe Caldeira
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication466718c9-2ab0-489f-88ec-a9e113c2e27b
relation.isAuthorOfPublication9b3258cd-a3d1-46f9-bc04-2bdd99d87014
relation.isAuthorOfPublicationb353121e-fa46-43fe-b4c0-5e9848084d17
relation.isAuthorOfPublicatione845705e-5b0b-4f70-9c53-c472ffd768d1
relation.isAuthorOfPublication.latestForDiscoveryb353121e-fa46-43fe-b4c0-5e9848084d17

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