Dirk Gorissen - Measuring and Predicting Departures from Routine in Human Mobility
448 views · Published 14 April 2014 · 41:59 · Indexed 15 October 2026
Channel: PyData · 2014 · People & Blogs
http://www.slideshare.net/PyData/measuring-and-predicting-departures-from-routine-in-human-mobility-dirk-gorissen Understanding human mobility patterns is a significant research endeavor that has recently received considerable attention. Developing the science to describe and predict how people move from one place to another during their daily lives promises to address a wide range of societal challenges: from predicting the spread of infectious diseases, improving urban planning, to devising effective emergency response strategies. This presentation will discuss a Bayesian framework to analyse an individual's mobility patterns and identify departures from routine. It is able to detect both spatial and temporal departures from routine based on heterogeneous sensor data (GPS, Cell Tower, social media, ..) and outperforms existing state-of-the-art predictors. Applications include mobile digital assistants (e.g., Google Now), mobile advertising (e.g., LivingSocial), and crowdsourcing physical tasks (e.g., TaskRabbit). 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
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