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BEGIN:VEVENT
UID:351@lincs.fr
DTSTART;TZID=Europe/Paris:20171129T140000
DTEND;TZID=Europe/Paris:20171129T150000
DTSTAMP:20171129T141257Z
URL:https://www.lincs.fr/events/predicting-user-qoe-from-qos-metrics-for-i
 nternet-applications-2/
SUMMARY:Predicting user QoE from QoS metrics for internet applications
DESCRIPTION:Predicting the user Quality-of-Experience (QoE) for an internet
 application is a highly desirable feature in a number of situations.
 However\, directly measuring user QoE is extremely challenging\, due to its
 subjective nature. One common approach is to measure Quality-of-Service
 (QoS) metrics and use it to predict user QoE. In this presentation\, we
 show our efforts into understanding and predicting user QoE. First\, we
 will discuss state-of-the-art quality assessment methodologies. Then\, we
 will present several approaches to model user QoE from QoS metrics.
 Finally\, we show a few examples where we model user QoE from QoS metrics.
CATEGORIES:Seminars,Youtube
LOCATION:LINCS Seminars room\, 23\, avenue d'Italie\, Paris\, 75013\,
 France
GEO:48.828400;2.356897
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23\, avenue d'Italie\,
 Paris\, 75013\, France;X-APPLE-RADIUS=100;X-TITLE=LINCS Seminars
 room:geo:48.828400,2.356897
END:VEVENT
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:STANDARD
DTSTART:20171029T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
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