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dc.provenanceCONICET-
dc.creatorPálovics, Róbert-
dc.creatorDaróczy, Bálint-
dc.creatorBenczúr, András-
dc.creatorPap, Julia-
dc.creatorErmann, Leonardo-
dc.creatorPhan, Samuel-
dc.creatorChepelianskii, Alexei D.-
dc.creatorShepelyansky, Dima L.-
dc.date2018-04-11T20:24:21Z-
dc.date2018-04-11T20:24:21Z-
dc.date2015-08-
dc.date2018-04-11T15:11:31Z-
dc.date.accessioned2019-04-29T15:35:53Z-
dc.date.available2019-04-29T15:35:53Z-
dc.date.issued2018-04-11T20:24:21Z-
dc.date.issued2018-04-11T20:24:21Z-
dc.date.issued2015-08-
dc.date.issued2018-04-11T15:11:31Z-
dc.identifierPálovics, Róbert; Daróczy, Bálint; Benczúr, András; Pap, Julia; Ermann, Leonardo; et al.; Statistical analysis of Nomao customer votes for spots of France; Springer; European Physical Journal B - Condensed Matter; 88; 8-2015; 194-204-
dc.identifier1434-6028-
dc.identifierhttp://hdl.handle.net/11336/41783-
dc.identifier1434-6036-
dc.identifierCONICET Digital-
dc.identifierCONICET-
dc.identifier.urihttp://rodna.bn.gov.ar:8080/jspui/handle/bnmm/297441-
dc.descriptionWe investigate the statistical properties of votes of customers for spots of France collected by the startup company Nomao. The frequencies of votes per spot and per customer are characterized by a power law distribution which remains stable on a time scale of a decade when the number of votes is varied by almost two orders of magnitude. Using the computer science methods we explore the spectrum and the eigenvalues of a matrix containing user ratings to geolocalized items. Eigenvalues nicely map to large towns and regions but show certain level of instability as we modify the interpretation of the underlying matrix. We evaluate imputation strategies that provide improved prediction performance by reaching geographically smooth eigenvectors. We point on possible links between distribution of votes and the phenomenon of self-organized criticality.-
dc.descriptionFil: Pálovics, Róbert. Hungarian Academy of Sciences; Hungría. Technical University Budapest; Hungría-
dc.descriptionFil: Daróczy, Bálint. Hungarian Academy of Sciences; Hungría. Technical University Budapest; Hungría-
dc.descriptionFil: Benczúr, András. Hungarian Academy of Sciences; Hungría. Eötvös University Budapest; Hungría-
dc.descriptionFil: Pap, Julia. Hungarian Academy of Sciences; Hungría-
dc.descriptionFil: Ermann, Leonardo. Comisión Nacional de Energía Atómica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina-
dc.descriptionFil: Phan, Samuel. Nomao; Francia-
dc.descriptionFil: Chepelianskii, Alexei D.. Université Paris Sud; Francia-
dc.descriptionFil: Shepelyansky, Dima L.. Centre National de la Recherche Scientifique; Francia-
dc.formatapplication/pdf-
dc.formatapplication/pdf-
dc.languageeng-
dc.publisherSpringer-
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1140/epjb/e2015-60357-1-
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1140%2Fepjb%2Fe2015-60357-1-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/-
dc.sourcereponame:CONICET Digital (CONICET)-
dc.sourceinstname:Consejo Nacional de Investigaciones Científicas y Técnicas-
dc.sourceinstacron:CONICET-
dc.source.urihttp://hdl.handle.net/11336/41783-
dc.subjectCOMPLEX NETWORKS-
dc.subjectRECOMMENDATION-
dc.subjectCiencias de la Computación-
dc.subjectCiencias de la Computación e Información-
dc.subjectCIENCIAS NATURALES Y EXACTAS-
dc.titleStatistical analysis of Nomao customer votes for spots of France-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.typeinfo:ar-repo/semantics/articulo-
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