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Laboratoire d'InfoRmatique en Image et Systèmes d'information

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Laboratoire d'InfoRmatique en Image et Systèmes d'information
UMR 5205 CNRS / INSA Lyon / Université Claude Bernard Lyon 1 / Université Lumière Lyon 2 / École Centrale de Lyon
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International conference with reviewing committee

Contextual Recommendation of Social Updates, a Tag-based Framework [PDF]
Adrien Joly [LIRIS] , Pierre Maret [LHC] , Johann Daigremont [Alcatel-Lucent Bell Labs France [Nozay]]
12/2010 (to be published)
Dans International Conference on Active Media Technology (AMT'10), Springer ed. Toronto, Canada.

HAL : hal-00531366

Abstract

In this paper, we propose a framework to improve the relevance of awareness information about people and subjects, by adapting recommendation techniques to real-time web data, in order to reduce information overload. The novelty of our approach relies on the use of contextual information about people's current activities to rank social updates which they are following on Social Networking Services and other collaborative software. The two hypothesis that we are supporting in this paper are: (i) a social update shared by person X is relevant to another person Y if the current context of Y is similar to X's context at time of sharing; and (ii) in a web-browsing session, a reliable current context of a user can be processed using metadata of web documents accessed by the user. We discuss the validity of these hypothesis by analyzing their results on experimental data.

BibTex

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@InProceedings{Liris-4747,
  title         = {{Contextual Recommendation of Social Updates, a Tag-based 
    Framework}},
  author        = {Adrien {Joly} and Pierre {Maret} and Johann {Daigremont}},
  year          = {2010},
  month         = dec,
  booktitle     = {International Conference on Active Media Technology 
    (AMT'10)},
  editor        = {Springer}, 
  language      = {en},
  url           = {http://liris.cnrs.fr/publis/?id=4747}
}