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dc.contributor.authorDe Maio, C
dc.contributor.authorGallo, M
dc.contributor.authorHao, F
dc.contributor.authorYang, E
dc.date.accessioned2021-04-26T09:51:41Z
dc.date.issued2020-07-11
dc.description.abstractAdvertising is becoming a business on social networks. Billions of people around the world use social media, and fastly, it has become one of the defining technologies of our time. Social platforms like Twitter are one of the primary means of communication and information dissemination and can capture the interest of potential customers. Therefore, it is crucial to select suitable advertisements to users in specific times and locations for capturing their attention, profitably. In this paper, we propose a context-aware advertising recommendation system that, by analyzing the users’ tweets and movements along a timeline, infers the personal interests of users and provides attractive ads to users through the triadic formal concept analysis theory.en_GB
dc.description.sponsorshipEuropean Union Horizon 2020en_GB
dc.identifier.citationVol. 25, pp. 379 - 387en_GB
dc.identifier.doi10.1007/s00500-020-05147-5
dc.identifier.grantnumberH2020-MSCAIF-2018-840922en_GB
dc.identifier.urihttp://hdl.handle.net/10871/125477
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.rights.embargoreasonUnder embargo until 11 July 2021 in compliance with publisher policyen_GB
dc.rights© Springer-Verlag GmbH Germany, part of Springer Nature 2020en_GB
dc.subjectTriadic concept analysisen_GB
dc.subjectTime-aware analysisen_GB
dc.subjectAds recommendationen_GB
dc.subjectLocation-based analysisen_GB
dc.titleWho and where: context-aware advertisement recommendation on Twitteren_GB
dc.typeArticleen_GB
dc.date.available2021-04-26T09:51:41Z
dc.identifier.issn1432-7643
dc.descriptionThis is the author accepted manuscript. The final version is available from Springer via the DOI in this recorden_GB
dc.identifier.journalSoft Computingen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2020-07-11
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-04-26T09:49:26Z
refterms.versionFCDAM
refterms.panelBen_GB


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