Recommender System: A Personalized TV Guide System

Ávila, Paulo Muniz de; Zorzo, Sergio Donizetti

doi:10.1007/978-3-642-20077-9_20

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Recommender Systems On Television2

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2014

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Cited by 1 publication

(2 citation statements)

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“…There are researches that propose solutions related directly to their television set [10,11,20], set-top boxes [2, 6, 10, 7, 20], through IPTV channels [9,8] or even as guides on the web [8,13]. For making recommendations, researches [2, 7,8,11,17] use collaborative filtering, researches [6,20] use content-based techniques and researches [10,13] a hybrid approach for achieving the expected result.…”

Section: Recommender Systems On Televisionmentioning

confidence: 99%

See 1 more Smart Citation

Unsupervised TV Scheduling Based on Collaborative Filtering

Freitas

Simon²,

Wangenheim

2014

Proceedings of the 20th Brazilian Symposium on Multimedia and the Web

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The generation of a television program schedule is a daily challenge. Broadcasting companies need to broadcast the best content according to the audience's preference. This paper proposes a novel take on collaborative filtering techniques to automate the selection of content based on viewers' rating through an interactive digital TV application. In order to overcome the fact that a television channel can broadcast only one schedule at a time, we group all ratings on Time Intervals in order to generalize viewers' preference and present the most appropriate content using a collaborative filtering technique.

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Section: Recommender Systems On Televisionmentioning

confidence: 99%

“…To help in this task, employment of recommender systems has been used as a solution [2, 6,10,7,8,11,17,20]. Researches on recommender systems in television have been mostly centered on helping viewers find the best programs available among the diversity of channels.…”

Section: Recommender Systems On Televisionmentioning

confidence: 99%