Assessing distributed collaborative recommendations in different opportunistic network scenarios

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dc.contributor.authorBARBOSA, L. N.
dc.contributor.authorGEMMELL, J. F.
dc.contributor.authorHORVATH, M.
dc.contributor.authorHEIMFARTH, T.
dc.date.accessioned2022-01-12T21:55:35Z
dc.date.available2022-01-12T21:55:35Z
dc.date.issued2020-08-01
dc.description.abstract© 2020 Inderscience Enterprises Ltd.Mobile devices are common throughout the world, even in countries with limited internet access and even when natural disasters disrupt access to a centralised infrastructure. This access allows for the exchange of information at an incredible pace and across vast distances. However, this wealth of information can frustrate users as they become inundated with irrelevant or unwanted data. Recommender systems help to alleviate this burden. In this work, we propose a recommender system where users share information via an opportunistic network. Each device is responsible for gathering information from nearby users and computing its own recommendations. An exhaustive empirical evaluation was conducted on two different data sets. Scenarios with different node densities, velocities and data exchange parameters were simulated. Our results show that in a relatively short time when a sufficient number of users are present, an opportunistic distributed recommender system achieves results comparable to that of a centralised architecture.
dc.description.firstpage646
dc.description.issuenumber5
dc.description.lastpage661
dc.description.volume11
dc.identifier.citationBARBOSA, L. N.; GEMMELL, J. F.; HORVATH, M.; HEIMFARTH, T. Assessing distributed collaborative recommendations in different opportunistic network scenarios. International Journal of Grid and Utility Computing, v. 11, n. 5, p. 646-661 aug. 2020.
dc.identifier.doi10.1504/IJGUC.2020.110052
dc.identifier.issn1741-8488
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/3668
dc.relation.ispartofInternational Journal of Grid and Utility Computing
dc.rightsAcesso Restrito
dc.subject.otherlanguageDecentralised recommender systems
dc.subject.otherlanguageDevice-to-device communications
dc.subject.otherlanguageMachine learning
dc.subject.otherlanguageMobile ad hoc networks
dc.subject.otherlanguageOpportunistic networks
dc.subject.otherlanguageRecommender systems
dc.subject.otherlanguageUser-based collaborative filtering
dc.titleAssessing distributed collaborative recommendations in different opportunistic network scenarios
dc.typeArtigo
fei.scopus.citations1
fei.scopus.eid2-s2.0-85092397394
fei.scopus.subjectCollaborative recommendation
fei.scopus.subjectEmpirical evaluations
fei.scopus.subjectExchange of information
fei.scopus.subjectExchange parameters
fei.scopus.subjectInternet access
fei.scopus.subjectNatural disasters
fei.scopus.subjectOpportunistic networks
fei.scopus.subjectWealth of information
fei.scopus.updated2024-05-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85092397394&origin=inward
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