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Data Mapping by Restricted Boltzmann Machines for Social Circles Detection

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Data Mapping by Restricted Boltzmann Machines for Social Circles Detection

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dc.contributor.author Alonso Nanclares, Jesús Alberto es_ES
dc.contributor.author Paredes Palacios, Roberto es_ES
dc.contributor.author Rosso, Paolo es_ES
dc.date.accessioned 2016-06-28T12:09:07Z
dc.date.available 2016-06-28T12:09:07Z
dc.date.issued 2015-07
dc.identifier.isbn 978-1-4799-1959-8
dc.identifier.issn 2161-4393
dc.identifier.uri http://hdl.handle.net/10251/66684
dc.description ©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. es_ES
dc.description.abstract Social circles detection is a special case of community detection in social network that is currently attracting a growing interest in the research community. In this paper, we propose a two-step technique, making emphasis on the mapping of the data by Restricted Boltzmann Machines (RBMs). Social circles are subsequently inferred by k-means over the preprocessed data. We define different vectorial representations from both structural egonet information and user profile features, and perform a set of tests to adjust the optimal parameters of the RBMs. We study and compare the performance on the ego-Facebook dataset of social circles from Facebook from the Stanford Large Network Dataset Collection. We compare our results with several different baselines. es_ES
dc.description.sponsorship This work was developed in the framework of the W911NF-14-1-0254 research project Social Copying Community Detection (SOCOCODE), funded by the US Army Research Office (ARO). es_ES
dc.format.extent 7 es_ES
dc.language Inglés es_ES
dc.publisher IEEE es_ES
dc.relation ARO/W911NF-14-1-0254 es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Data Mapping by Restricted Boltzmann Machines for Social Circles Detection es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1109/IJCNN.2015.7280653
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Alonso Nanclares, JA.; Paredes Palacios, R.; Rosso, P. (2015). Data Mapping by Restricted Boltzmann Machines for Social Circles Detection. IEEE. doi:10.1109/IJCNN.2015.7280653 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename International Joint Conference on Neural Networks (IJCNN 2015) es_ES
dc.relation.conferencedate July 12-17, 2015 es_ES
dc.relation.conferenceplace Killarney, Irlanda es_ES
dc.relation.publisherversion http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7256526 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 306167 es_ES
dc.contributor.funder Army Research Office, EEUU es_ES


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