A collaborative filtering approach to personalized interactive entertainment using MPEG-21

Andreou, G; Mylonas, P; Karpouzis, K

dc.contributor.author	Andreou, G	en
dc.contributor.author	Mylonas, P	en
dc.contributor.author	Karpouzis, K	en
dc.date.accessioned	2014-03-01T02:51:00Z
dc.date.available	2014-03-01T02:51:00Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35291
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-67649830896&partnerID=40&md5=8f473be383ad8bafb54774248ae396fb	en
dc.subject	Collaborative filtering	en
dc.subject	Digital item	en
dc.subject	MPEG-21	en
dc.subject	Network management adaptation	en
dc.subject	Personalization	en
dc.subject.other	Collaborative filtering	en
dc.subject.other	Collaborative filtering algorithms	en
dc.subject.other	Content-adaptive	en
dc.subject.other	Digital item	en
dc.subject.other	End-users	en
dc.subject.other	Hier-archical clustering	en
dc.subject.other	Hierarchical clustering algorithms	en
dc.subject.other	Integrated frameworks	en
dc.subject.other	Interactive entertainment	en
dc.subject.other	Interactive services	en
dc.subject.other	MPEG-21	en
dc.subject.other	MPEG-21 Standard	en
dc.subject.other	Multimedia contents	en
dc.subject.other	Personalization	en
dc.subject.other	Research efforts	en
dc.subject.other	Use case scenario	en
dc.subject.other	Bubbles (in fluids)	en
dc.subject.other	Clustering algorithms	en
dc.subject.other	Information systems	en
dc.subject.other	Knowledge representation	en
dc.subject.other	Motion Picture Experts Group standards	en
dc.subject.other	Signal filtering and prediction	en
dc.subject.other	World Wide Web	en
dc.subject.other	Network management	en
dc.title	A collaborative filtering approach to personalized interactive entertainment using MPEG-21	en
heal.type	conferenceItem	en
heal.publicationDate	2007	en
heal.abstract	In this paper we present an integrated framework for personalized access to interactive entertainment content, using characteristics from the emerging MPEG-21 standard. Our research efforts focus on multimedia content presented within the framework set by today's movie content broadcasting over a variety of networks and terminals. This work contributes to the bridging of the gap between the content and the user, providing end-users with a wide range of real-time interactive services, ranging from plain personalized statistics and optional enhanced in-play visual enhancements to a fully user- and content-adaptive platform. The proposed approach implements and extends a well-known collaborative filtering approach; it applies a hierarchical clustering algorithm on the data towards the scope of group modelling implementation. It illustrates also the benefits from the MPEG-21 components utilization in the process and analyzes the importance of the Digital Item concept. Finally, a use case scenario is presented to illustrate the entire procedure. The core of this work is the novel group modelling approach, on top of the hybrid collaborative filtering algorithm, employing principles of taxonomic knowledge representation and hierarchical clustering theory. The outcome of this framework design is that end-users enhance their personalized viewing experience.	en
heal.journalName	Webist 2007 - 3rd International Conference on Web Information Systems and Technologies, Proceedings	en
dc.identifier.volume	IT	en
dc.identifier.spage	222	en
dc.identifier.epage	227	en