Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/19190

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dc.contributor.authorSantos, Maribel Yasmina-
dc.date.accessioned2012-05-09T10:29:42Z-
dc.date.available2012-05-09T10:29:42Z-
dc.date.issued2012-04-
dc.identifier.urihttp://hdl.handle.net/1822/19190-
dc.description.abstractThis paper presents some of the challenges that arise in the analysis of data associated to RADIUS logs, looking at movement patterns that can be identified using data mining algorithms. When talking about movement, space is inherent to the places visited by groups of individuals. However, no absolute reference to a geographic position exists in these data. The position of the Wi-Fi nodes gives some semantic about the places where people are, but does not allow the verification if two nodes are, for example, near each other. This paper describes the work developed so far in the process of analysis of such complex data set. The steps of the knowledge discovery in databases process were applied in order to verify if traditional data mining algorithms can be used in the analysis of RADIUS logs to identify places that are visited in the same sequence by several users. The obtained results show that the association rules technique can be used to identify places that are visited in a similar way by groups of individuals.por
dc.description.sponsorshipThis project was supported by the Portuguese Science and Technology Foundation (FCT - Fundação para a Ciência e Tecnologia), under project SUM (Sensing and Understanding human Motion dynamics, PTDC/EIA-EIA/113933/2009). This work was partly funded by FEDER funds through the Operational Competitiveness Program (COMPETE) and by FCT with the project: FCOMP-01-0124-FEDER-022674.por
dc.language.isoengpor
dc.rightsopenAccesspor
dc.subjectData miningpor
dc.subjectRadius datapor
dc.subjectAssociation rulespor
dc.subjectMovement patternspor
dc.titleMining RADIUS data : how to detect movement patterns?por
dc.typeconferencePaperpor
dc.peerreviewedyespor
sdum.publicationstatuspublishedpor
oaire.citationStartPage14por
oaire.citationEndPage17por
oaire.citationConferencePlaceAvignon, Francepor
oaire.citationTitleComplex Data Mining in a GeoSpatial Context Workshop, 15th AGILE International Conference on Geographic Information Sciencepor
sdum.conferencePublicationComplex Data Mining in a GeoSpatial Context Workshop, 15th AGILE International Conference on Geographic Information Sciencepor
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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