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Author De Marez, Lieven ♦ Mechant, Peter ♦ Courtois, Cédric ♦ Verdejo, Adrian Juan ♦ Martens, Luc ♦ De Moor, Katrien ♦ De Pessemier, Toon
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Objective and subjective user feedback ♦ Youtube ♦ Facebook application ♦ Personaltv ♦ User evaluation ♦ Online video ♦ Recommender systems
Abstract The overabundance of content on online video platforms has made intelligent recommender systems that assist users in finding content matching their personal preferences indispensable. This article reports on a study in which “PersonalTV,” an online video recommendation application that has been developed for research purposes, was evaluated by a panel of test users for the first time. In view of this, objective implicit and subjective explicit user feedback were triangulated. The “PersonalTV” application enables its users to explore and watch videos from the YouTube library. It builds up a personal viewing profile in order to give personalized content suggestions. We investigated the relation between the recommended content and the consumption percentage (RQ 1), between the recommended content and the reported satisfaction (RQ 2), and explored whether these objective and subjective measures converge (RQ 3). Additional user feedback that may help to improve the application was collected.
Description Affiliation: Ghent University, Ghent/Belgium (De Moor, Katrien; De Pessemier, Toon; Mechant, Peter; Courtois, Cédric; Verdejo, Adrian Juan; De Marez, Lieven; Martens, Luc)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-03-01
Publisher Place New York
Journal Computers in Entertainment (CIE) (CIE)
Volume Number 9
Issue Number 3
Page Count 22
Starting Page 1
Ending Page 22

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Source: ACM Digital Library