Employing clustering algorithms to create user groups for personalized context aware services provision

Voulodimos, AS; Patrikakis, CZ; Karamolegkos, PN; Doulamis, AD; Sardis, ES

dc.contributor.author	Voulodimos, AS	en
dc.contributor.author	Patrikakis, CZ	en
dc.contributor.author	Karamolegkos, PN	en
dc.contributor.author	Doulamis, AD	en
dc.contributor.author	Sardis, ES	en
dc.date.accessioned	2014-03-01T02:53:15Z
dc.date.available	2014-03-01T02:53:15Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36193
dc.subject	Context aware services	en
dc.subject	Social networks	en
dc.subject	Spectral clustering	en
dc.subject	User groups	en
dc.subject	User profile	en
dc.subject.other	Context aware services	en
dc.subject.other	Social Networks	en
dc.subject.other	Spectral clustering	en
dc.subject.other	User groups	en
dc.subject.other	User profile	en
dc.subject.other	Cobalt compounds	en
dc.subject.other	Multimedia services	en
dc.subject.other	Clustering algorithms	en
dc.title	Employing clustering algorithms to create user groups for personalized context aware services provision	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/2072627.2072637	en
heal.identifier.secondary	http://dx.doi.org/10.1145/2072627.2072637	en
heal.publicationDate	2011	en
heal.abstract	The successful provision of context aware services entails the attainment of equilibrium between the extent of personalization desired and the user's need for privacy. Two are the major elements that play a significant role: the user's location and the user's preferences. In this paper we focus on the latter, and propose to employ a social groups' creation methodology, so as to hierarchically organize the user preferences concerning any domain in different levels of detail. We describe some notions and metrics which play a key role in social networking frameworks, and we perform an evaluation study of three widely used clustering methods (k-means, hierarchical and spectral clustering) in the scope of social groups assessment and in regard to the cardinality of the profile used to assess users' preferences. The results of the work can be used in many applications, including personalized media delivery, offering a framework on which next generation multimedia access can be provided. © 2011 ACM.	en
heal.journalName	MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - ACM Workshop on Social Behavioural Networked Media Access 2011, SBNMA'11	en
dc.identifier.doi	10.1145/2072627.2072637	en
dc.identifier.spage	33	en
dc.identifier.epage	38	en