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UID:50@lincs.fr
DTSTART;TZID=Europe/Paris:20160706T140000
DTEND;TZID=Europe/Paris:20160706T150000
DTSTAMP:20170313T170915Z
URL:https://www.lincs.fr/events/mining-usage-patterns-in-residential-intra
 net-of-things/
SUMMARY:Mining usage patterns in residential intranet of things
DESCRIPTION:Ubiquitous smart technologies gradually transform modern homes
 into Intranet of Things\, where a multitude of connected devices allow for
 novel home automation services (e.g.\, energy or bandwidth savings\,
 comfort enhancement\, etc.). Optimizing and enriching the Quality of
 Experience (QoE) of residential users emerges as a critical differentiator
 for Internet and Communication Service providers (ISPs and CSPs\,
 respectively) and heavily relies on the analysis of various kinds of data
 (connectivity\, performance\,usage) gathered from home networks. In this
 paper\, we are interested in new Machine-to-Machine data analysis
 techniques that go beyond binary association rule mining for traditional
 market basket analysis considered by previous works\, to analyze individual
 device logs of home gateways. Based on multidimensional patterns mining
 framework\, we extract complex device co-usage patterns of 201 residential
 broadband users of an ISP\, subscribed to a triple-play service. Such
 fine-grained device usage patternsprovide valuable insights for emerging
 use cases such as an adaptive usage of home devices\, and also ``things''
 recommendation.
CATEGORIES:Seminars,Youtube
LOCATION:LINCS Meeting Room 40\, 23\, avenue d'Italie\, Paris\, 75013\,
 France
GEO:48.8283983;2.3568972000000485
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 40:geo:48.8283983,2.3568972000000485
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
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DTSTART:20160327T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
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