%0 Generic %1 Farrahi_discoveringhuman %A Farrahi, Katayoun %A Gatica-perez, Daniel %D 2010 %K clustering toread %T Discovering Human Routines from Cell Phone Data with Topic Models %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.5105 %X We present a framework to automatically discover people’s routines from information extracted by cell phones. The framework is built from a probabilistic topic model learned on novel bag type representations of activity-related cues (location, proximity and their temporal variations over a day) of peoples ’ daily routines. Using real-life data from the Reality Mining dataset, covering 68 000+ hours of human activities, we can successfully discover location-driven (from cell tower connections) and proximity-driven (from Bluetooth information) routines in an unsupervised manner. The resulting topics meaningfully characterize some of the underlying co-occurrence structure of the activities in the dataset, including “going to work early/late”, “being home all day”, “working constantly”, “working sporadically” and “meeting at lunch time”. 1.

@misc{Farrahi_discoveringhuman, abstract = {We present a framework to automatically discover people’s routines from information extracted by cell phones. The framework is built from a probabilistic topic model learned on novel bag type representations of activity-related cues (location, proximity and their temporal variations over a day) of peoples ’ daily routines. Using real-life data from the Reality Mining dataset, covering 68 000+ hours of human activities, we can successfully discover location-driven (from cell tower connections) and proximity-driven (from Bluetooth information) routines in an unsupervised manner. The resulting topics meaningfully characterize some of the underlying co-occurrence structure of the activities in the dataset, including “going to work early/late”, “being home all day”, “working constantly”, “working sporadically” and “meeting at lunch time”. 1.}, added-at = {2010-09-20T16:20:29.000+0200}, author = {Farrahi, Katayoun and Gatica-perez, Daniel}, biburl = {https://www.bibsonomy.org/bibtex/24c905f2cfc5e88c271ebc4f10d47de30/hotho}, description = {Discovering Human Routines from Cell Phone Data with Topic Models}, interhash = {5e3f9c64f6fb9ba5226e3345acd3ddd8}, intrahash = {4c905f2cfc5e88c271ebc4f10d47de30}, keywords = {clustering toread}, timestamp = {2010-09-20T16:20:29.000+0200}, title = {Discovering Human Routines from Cell Phone Data with Topic Models}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.5105}, year = 2010 }