Personalization on a peer-to-peer television system
We introduce personalization on Tribler , a peer-to-peer (P2P) television system. Personalization allows users to browse programs much more efficiently according to their taste. It also enables to build social networks that can improve the performance of current P2P systems considerably, by increasi...
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| Veröffentlicht in: | Multimedia tools and applications 2008-01, Vol.36 (1-2), p.89-113 |
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| container_title | Multimedia tools and applications |
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| creator | Wang, Jun Pouwelse, Johan Fokker, Jenneke de Vries, Arjen P. Reinders, Marcel J. T. |
| description | We introduce personalization on
Tribler
, a peer-to-peer (P2P) television system. Personalization allows users to browse programs much more efficiently according to their taste. It also enables to build social networks that can improve the performance of current P2P systems considerably, by increasing content availability, trust and the realization of proper incentives to exchange content. This paper presents a novel scheme, called
BuddyCast
, that builds such a social network for a user by exchanging user interest profiles using exploitation and exploration principles. Additionally, we show how the interest of a user in TV programs can be predicted from the zapping behavior by the introduced user-item relevance models, thereby avoiding the explicit rating of TV programs. Further, we present how the social network of a user can be used to realize a truly distributed recommendation of TV programs. Finally, we demonstrate a novel user interface for the personalized peer-to-peer television system that encompasses a personalized tag-based navigation to browse the available distributed content. The user interface also visualizes the social network of a user, thereby increasing community feeling which increases trust amongst users and within available content and creates incentives of to exchange content within the community. |
| doi_str_mv | 10.1007/s11042-006-0075-6 |
| format | Article |
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Tribler
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BuddyCast
, that builds such a social network for a user by exchanging user interest profiles using exploitation and exploration principles. Additionally, we show how the interest of a user in TV programs can be predicted from the zapping behavior by the introduced user-item relevance models, thereby avoiding the explicit rating of TV programs. Further, we present how the social network of a user can be used to realize a truly distributed recommendation of TV programs. Finally, we demonstrate a novel user interface for the personalized peer-to-peer television system that encompasses a personalized tag-based navigation to browse the available distributed content. The user interface also visualizes the social network of a user, thereby increasing community feeling which increases trust amongst users and within available content and creates incentives of to exchange content within the community.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-006-0075-6</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Archives & records ; Computer Communication Networks ; Computer Science ; Customization ; Data Structures and Information Theory ; Multimedia Information Systems ; Peer to peer computing ; Recommender systems ; Social networks ; Special Purpose and Application-Based Systems ; Studies ; Television programs</subject><ispartof>Multimedia tools and applications, 2008-01, Vol.36 (1-2), p.89-113</ispartof><rights>Springer Science+Business Media, LLC 2007</rights><rights>Springer Science+Business Media, LLC 2008</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c455t-a65f11e7dc0a746d18f3bb3b95a9853be59807f22aa56ee1af07c32d143a0fc83</citedby><cites>FETCH-LOGICAL-c455t-a65f11e7dc0a746d18f3bb3b95a9853be59807f22aa56ee1af07c32d143a0fc83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11042-006-0075-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-006-0075-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Wang, Jun</creatorcontrib><creatorcontrib>Pouwelse, Johan</creatorcontrib><creatorcontrib>Fokker, Jenneke</creatorcontrib><creatorcontrib>de Vries, Arjen P.</creatorcontrib><creatorcontrib>Reinders, Marcel J. T.</creatorcontrib><title>Personalization on a peer-to-peer television system</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>We introduce personalization on
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BuddyCast
, that builds such a social network for a user by exchanging user interest profiles using exploitation and exploration principles. Additionally, we show how the interest of a user in TV programs can be predicted from the zapping behavior by the introduced user-item relevance models, thereby avoiding the explicit rating of TV programs. Further, we present how the social network of a user can be used to realize a truly distributed recommendation of TV programs. Finally, we demonstrate a novel user interface for the personalized peer-to-peer television system that encompasses a personalized tag-based navigation to browse the available distributed content. 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Tribler
, a peer-to-peer (P2P) television system. Personalization allows users to browse programs much more efficiently according to their taste. It also enables to build social networks that can improve the performance of current P2P systems considerably, by increasing content availability, trust and the realization of proper incentives to exchange content. This paper presents a novel scheme, called
BuddyCast
, that builds such a social network for a user by exchanging user interest profiles using exploitation and exploration principles. Additionally, we show how the interest of a user in TV programs can be predicted from the zapping behavior by the introduced user-item relevance models, thereby avoiding the explicit rating of TV programs. Further, we present how the social network of a user can be used to realize a truly distributed recommendation of TV programs. Finally, we demonstrate a novel user interface for the personalized peer-to-peer television system that encompasses a personalized tag-based navigation to browse the available distributed content. The user interface also visualizes the social network of a user, thereby increasing community feeling which increases trust amongst users and within available content and creates incentives of to exchange content within the community.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s11042-006-0075-6</doi><tpages>25</tpages><oa>free_for_read</oa></addata></record> |
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| source | SpringerLink Journals |
| subjects | Archives & records Computer Communication Networks Computer Science Customization Data Structures and Information Theory Multimedia Information Systems Peer to peer computing Recommender systems Social networks Special Purpose and Application-Based Systems Studies Television programs |
| title | Personalization on a peer-to-peer television system |
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