Detecting Contexts on the Desktop Using Bayesian Networks

Stefania Costache, Julien Gaugaz, Ekaterini Ioannou, Claudia Niederée, and Wolfgang Nejdl
In DESKTOP Search Workshop, co-located with SIGIR, July 2010, Geneva, Switzerland.
pdf

Abstract

A good understanding of a user's (working) contexts provides the basis for improved desktop information management, as well as for personalized desktop and Web search. We propose to combine a variety of evidences found by analyzing desktop information for inferring the user's working contexts, and more specifically infer file-to-context assignment using a Bayesian Network. Our preliminary experiments focus on identifying a good selection of evidences to use and show that the choice of evidences is coherent with user assessments for desktop files, as well as the contexts inferred by the Bayesian Network.

Bibtex

@inproceedings{conf/DesktopSearch/CostacheGINN10,
     author = {Stefania Costache and Julien Gaugaz and Ekaterini Ioannou and Claudia Nieder{\'e}e and Wolfgang Nejdl},
     title = {Detecting Contexts on the Desktop Using Bayesian Networks},
     booktitle = {DESKTOP Search Workshop co-located with SIGIR},
     year = {2010}
}