On exploiting social relationship and personal background for content discovery in P2P networks

Han, Xiao; Cuevas Rumín, Ángel; Crespi, Noël; Cuevas Rumín, Rubén; Huang, Xiaodi

Publication:
On exploiting social relationship and personal background for content discovery in P2P networks

dc.affiliation.dpto	UC3M. Departamento de Ingeniería Telemática	es
dc.affiliation.grupoinv	UC3M. Grupo de Investigación: Network Technologies	es
dc.contributor.author	Han, Xiao
dc.contributor.author	Cuevas Rumín, Ángel
dc.contributor.author	Crespi, Noël
dc.contributor.author	Cuevas Rumín, Rubén
dc.contributor.author	Huang, Xiaodi
dc.contributor.funder	European Commission	en
dc.contributor.funder	Ministerio de Economía y Competitividad (España)	es
dc.date.accessioned	2023-05-31T10:40:32Z
dc.date.available	2023-05-31T10:40:32Z
dc.date.issued	2014-11
dc.description.abstract	Content discovery is a critical issue in unstructured Peer-to-Peer (P2P) networks as nodes maintain only local network information. However, similarly without global information about human networks, one still can find specific persons via his/her friends by using social information. Therefore, in this paper, we investigate the problem of how social information (i.e., friends and background information) could benefit content discovery in P2P networks. We collect social information of 384,494 user profiles from Facebook, and build a social P2P network model based on the empirical analysis. In this model, we enrich nodes in P2P networks with social information and link nodes via their friendships. Each node extracts two types of social features – Knowledge and Similarity – and assigns more weight to the friends that have higher similarity and more knowledge. Furthermore, we present a novel content discovery algorithm which can explore the latent relationships among a node’s friends. A node computes stable scores for all its friends regarding their weight and the latent relationships. It then selects the top friends with higher scores to query content. Extensive experiments validate performance of the proposed mechanism. In particular, for personal interests searching, the proposed mechanism can achieve 100% of Search Success Rate by selecting the top 20 friends within two-hop. It also achieves 6.5 Hits on average, which improves 8x the performance of the compared methods.	en
dc.description.sponsorship	This work has been funded by the European Union under the project eCOUSIN (EU-FP7-318398) and the project SITAC (ITEA2-11020). It also has been partially funded by the Spanish Government through the MINEC eeCONTENT project (TEC2011-29688-C02-02).	en
dc.format.extent	13
dc.identifier.bibliographicCitation	Han, X., Cuevas, Á., Crespi, N., Cuevas, R., & Huang, X. (2014). On exploiting social relationship and personal background for content discovery in P2P networks. Future Generation Computer Systems, 40, 17-29.	en
dc.identifier.doi	https://doi.org/10.1016/j.future.2014.06.007
dc.identifier.issn	0167-739X
dc.identifier.publicationfirstpage	17
dc.identifier.publicationlastpage	29
dc.identifier.publicationtitle	Future Generation Computer Systems	en
dc.identifier.publicationvolume	40
dc.identifier.uri	https://hdl.handle.net/10016/37395
dc.identifier.uxxi	AR/0000015605
dc.language.iso	eng	en
dc.publisher	Elsevier	en
dc.relation.projectID	Gobierno de España. TEC2011-29688-C02-02	es
dc.relation.projectID	info:eu-repo/grantAgreement/EC/FP7-ICT-318398
dc.rights	© 2014 Elsevier B.V.	en
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España	*
dc.rights.accessRights	open access	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/	*
dc.subject.eciencia	Ciencias de la Información	es
dc.subject.eciencia	Informática	es
dc.subject.eciencia	Telecomunicaciones	es
dc.subject.other	Social P2P	en
dc.subject.other	Content discovery	en
dc.subject.other	Similarity	en
dc.subject.other	Knowledge	en
dc.title	On exploiting social relationship and personal background for content discovery in P2P networks	en
dc.type	research article	*
dc.type.hasVersion	AM	*
dspace.entity.type	Publication