| Document Date: 2014-03-07 06:47:36
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City Barcelona / L. A. / Toronto / / Company Telefonica / Whittaker / Tyler / Microsoft / Google Inc. / / Continent North America / Europe / / Country United States / Canada / / Currency USD / EUR / / / Facility Carnegie Mellon University / / IndustryTerm machine learning algorithms / privacy-preserving machine-learning algorithm / Internet-based mobile messaging applications / e.g. recommender systems / instant messaging services / mobile messaging solutions / usable solution / particular solution / weka data mining software / mobile instant messaging applications / pervasive mobile Internet access / mobile applications / mobile instant messaging services / online-status / social networks / online survey / online activity / / NaturalFeature Random forests / / OperatingSystem Android / / Organization Carnegie Mellon University / / Person Nuria Oliver / Rodrigo de Oliveira / Hudson / / Position mobile instant messenger / office worker / Butler / messenger / Harper / Author / *The author / / Product Message Monitor / Weka / Message Monitor / a background mobile service / / ProvinceOrState Oregon / / PublishedMedium Machine Learning / / Technology machine learning algorithms / SMS / smartphone / mobile phones / instant messaging / machine learning / Android / html / Mobile Devices / cellular telephone / privacy-preserving machine-learning algorithm / smartphones / data mining / / URL http /
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Didn’t You See My Message? Predicting Attentiveness to Mobile Instant Messages Martin Pielot, Rodrigo de Oliveira∗, Haewoon Kwak, Nuria Oliver Telefonica Research, Barcelona, Spain *The author is currently affiliated