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Personalised Combination of Multi-Source Data for User Profiling

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dc.contributor.authorVeloso, Bruno
dc.contributor.authorLeal, Fátima
dc.contributor.authorMalheiro, Benedita
dc.date.accessioned2022-05-11T10:46:14Z
dc.date.available2025-01-01T01:30:48Z
dc.date.issued2022
dc.description.abstractHuman interaction with intelligent systems, services and devices generates large volumes of user-related data. This multi-source information can be used to build richer user profiles and improve personalisation. Our goal is to combine multi-source user-related data to create user profiles by assigning dynamic individual weights to the different sources. This paper describes the proposed multi-source user profiling methodology and illustrates its application with a film recommendation system. The contemplated data sources include: (i) personal history, (ii) explicit preferences (ratings); and (iii) social activities (likes, comments or shares). The MovieLens dataset was selected and adapted to assess our approach by comparing the recommendations generated with the standard and the proposed methodologies. In the standard approach, we calculate the best global weights to apply to the different profile sources and generate all user profiles, accordingly. In the proposed approach, we determine, for each user, individual weights for the different profile sources to combine the available data and build the user profile. As a whole, our approach proved to be an efficient solution to a complex problem by continuously updating the individual data source weights and improving the accuracy of the generated personalised multimedia recommendations.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-981-16-7618-5_60pt_PT
dc.identifier.isbn978-981-16-7617-5
dc.identifier.urihttp://hdl.handle.net/10400.22/20494
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relation.ispartofseriesLecture Notes in Networks and Systems;60
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-981-16-7618-5_60pt_PT
dc.subjectUser Modellingpt_PT
dc.subjectMulti-sourcept_PT
dc.subjectProfilingpt_PT
dc.subjectRecommendationpt_PT
dc.titlePersonalised Combination of Multi-Source Data for User Profilingpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceSingaporept_PT
oaire.citation.endPage717pt_PT
oaire.citation.startPage707pt_PT
oaire.citation.titleProceedings of International Conference on Information Technology and Applicationspt_PT
oaire.citation.volume350pt_PT
person.familyNameLeal
person.familyNameBENEDITA CAMPOS NEVES MALHEIRO
person.givenNameFátima
person.givenNameMARIA
person.identifier.ciencia-id2211-3EC7-B4B6
person.identifier.ciencia-id7A15-08FC-4430
person.identifier.orcid0000-0003-4418-2590
person.identifier.orcid0000-0001-9083-4292
person.identifier.ridY-3460-2019
person.identifier.scopus-author-id57190765181
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication8e77ca2d-3cb2-4346-927b-a706a5580c9e
relation.isAuthorOfPublicationbabd4fda-654a-4b59-952d-6113eebbb308
relation.isAuthorOfPublication.latestForDiscoverybabd4fda-654a-4b59-952d-6113eebbb308

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