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Methodology for knowledge extraction from mobility big data

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dc.contributor.authorFerreira, João C.
dc.contributor.authorMonteiro, Vitor
dc.contributor.authorAfonso, José
dc.contributor.authorAfonso, Joao L.
dc.date.accessioned2019-03-07T11:03:57Z
dc.date.available2019-03-07T11:03:57Z
dc.date.issued2016
dc.description.abstractThe spread of mobile devices with several sensors, together with mobile communication, provides huge volumes of real-time data (big data) about users' mobility habits, which should be correctly analysed to extract useful knowledge. In our research we explore a data mining approach based on a Naive Bayes (NB) classifier applied to different sources of big data. To achieve this goal, we propose a methodology based on four processes that collects data and merges different data sources into pre-defined data classes. We can apply this methodology to different big data sources and extract a diversity of knowledge that can be applied to the development of dedicated applications and decision processes in the area of intelligent transportation systems, such as route advice, CO2 emissions reduction through fuel savings, and provision of smart advice for public transportation usage.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFERREIRA, João C.; [et al] – Methodology for knowledge extraction from mobility big data. In 13th International Conference on Distributed Computing and Artificial Intelligence (DCAI). Sevilla, Spain: Springer, 2016. ISBN 978-3-319-40161-4. Vol. 474/Pp. 97-105pt_PT
dc.identifier.doi10.1007/978-3-319-40162-1_11pt_PT
dc.identifier.isbn978-3-319-40161-4
dc.identifier.isbn978-3-319-40162-1
dc.identifier.issn2194-5357
dc.identifier.urihttp://hdl.handle.net/10400.21/9662
dc.language.isoengpt_PT
dc.publisherSpringerpt_PT
dc.subjectBig datapt_PT
dc.subjectData miningpt_PT
dc.subjectNaive bayespt_PT
dc.subjectMobile devicept_PT
dc.subjectSensor informationpt_PT
dc.titleMethodology for knowledge extraction from mobility big datapt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceJun 01-03, 2016 - Sevilla, Spainpt_PT
oaire.citation.endPage105pt_PT
oaire.citation.startPage97pt_PT
oaire.citation.title13th International Conference on Distributed Computing and Artificial Intelligence (DCAI)pt_PT
oaire.citation.volume474pt_PT
person.familyNamemonteiro
person.familyNameAfonso
person.familyNameAfonso
person.givenNamevitor
person.givenNameJosé
person.givenNameJoao L.
person.identifier.ciencia-idD115-ED90-E00A
person.identifier.ciencia-id981A-9C7D-B84E
person.identifier.ciencia-id1810-4130-7A3B
person.identifier.orcid0000-0001-6640-8955
person.identifier.orcid0000-0001-6275-9467
person.identifier.orcid0000-0001-9195-1239
person.identifier.ridD-4306-2012
person.identifier.ridK-3949-2012
person.identifier.ridD-8565-2012
person.identifier.scopus-author-id36696704200
person.identifier.scopus-author-id15062391700
person.identifier.scopus-author-id7005436406
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication.latestForDiscovery2efb4159-b1b3-4571-9eda-aafe8c833a5f

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