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dc.contributor.authorRamos, João Ricardo Martinspor
dc.contributor.authorAnalide, Cesarpor
dc.contributor.authorNeves, Josépor
dc.contributor.authorNovais, Paulopor
dc.date.accessioned2018-02-15T12:25:18Z-
dc.date.available2018-02-15T12:25:18Z-
dc.date.issued2017-
dc.identifier.citationRamos J., César A., Neves J., Novais P., Adapting the User Path Through Trajectory Data Mining, Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2017), Springer - Advances in Intelligent Systems and Computing, Vol 615, ISSN 2194-5357, ISBN 9783319401133, pp 210-202, 2017. https://doi.org/10.1007/978-3-319-61118-1_24por
dc.identifier.isbn978-3-319-61117-4-
dc.identifier.issn2194-5357por
dc.identifier.urihttps://hdl.handle.net/1822/50519-
dc.description.abstractThe pervasiveness of location based services such the GPS on mobile devices enabled the gathering of massive spatial-temporal data. These databases enabled the mining of new data in order to calculate frequent patterns and predict the movement of the objects. In the development of our system for guiding the user with cognitive disabilities (CogHelper) we are applying a trajectory data mining to adapt and adjust the path to user preferences. Indeed, the guiding process may be more useful and it increases the quality of life of the user through this new functionality (conciliated with the speculative computation module). Thus, instead of the user having to adapt to the application we are developing a system that adapts the path to the user. Rather than being guided through the shortest path he may be oriented by a longer but preferred path. The main contribution of this paper is the specification of the trajectory data mining which is incorporated in CogHelper system.por
dc.description.sponsorshipThis work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e a Tecnologia within the Project Scope: UID/CEC/00319/2013. The work of João Ramos is supported by a FCT doctoral grant with the reference SFRH/BD/89530/2012.por
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationPOCI-01-0145-FEDER-007043por
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F89530%2F2012/PTpor
dc.rightsopenAccesspor
dc.subjectTrajectory Data Miningpor
dc.subjectFrequent Patternspor
dc.subjectSequence Miningpor
dc.subjectClusteringpor
dc.titleAdapting the user path through trajectory data miningpor
dc.typeconferencePaperpor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007%2F978-3-319-61118-1_24por
oaire.citationStartPage195por
oaire.citationEndPage202por
oaire.citationConferencePlacePorto, Portugalpor
oaire.citationVolume615por
dc.identifier.eissn978-3-319-61118-1-
dc.identifier.doi10.1007/978-3-319-61118-1_24por
dc.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
dc.subject.wosScience & Technologypor
sdum.journalAdvances in Intelligent Systems and Computingpor
sdum.conferencePublicationAmbient intelligence: software and applications : 8th International Symposium on Ambient Intelligence (ISAmI 2017)por
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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