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Classification and prediction of whereabouts patterns from the Reality Mining dataset
15 references·0 citing·42 second hop
Classification and prediction of whereabouts patterns from the Reality Mining dataset (2012)Classification and prediction of whereabo…Extracting urban patterns from location-based social networks (2011)Extracting urban patterns fro…Discovering daily routines from Google Latitude with topic models (2011)Discovering daily routines fr…Probabilistic Mining of Socio-Geographic Routines From Mobile Phone Data (2010)Probabilistic Mining of Socio…Predicting human behaviour from selected mobile phone data points (2010)Predicting human behaviour fr…Eigenplaces: Segmenting Space through Digital Signatures (2009)Eigenplaces: Segmenting Space…Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network (2009)Eigenplaces: Analysing Cities…Eigenbehaviors: identifying structure in routine (2009)Eigenbehaviors: identifying s…Eigenbehaviors: identifying structure in routine (2009)Eigenbehaviors: identifying s…Supporting location-aware services for mobile users with the whereabouts diary (2008)Supporting location-aware ser…Daily Routine Classification from Mobile Phone Data (2008)Daily Routine Classification …Supporting Location-Aware Services for Mobile Users with the Whereabouts Diary (2007)Supporting Location-Aware Ser…MyLifeBits (2006)MyLifeBitsMobility Detection Using Everyday GSM Traces (2006)Mobility Detection Using Ever…Farther Than You May Think: An Empirical Investigation of the Proximity of Users to Their Mobile Phones (2006)Farther Than You May Think: A…Extracting places from traces of locations (2004)Extracting places from traces…Inferring High-Level Behavior from Low-Level Sensors (2003)Reality mining: sensing complex social systems (2005)Understanding and capturing people’s privacy policies in a mobile social networking application (2008)Mining Individual Life Pattern Based on Location History (2009)Discovering routines from large-scale human locations using probabilistic topic models (2011)Using GPS to learn significant locations and predict movement across multiple users (2003)Discovering personally meaningful places (2007)Learning and inferring transportation routines (2007)Data from mobile phone operators: A tool for smarter cities? (2014)Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students (2017)Revealing travel patterns and city structure with taxi trip dataCellular Census: Explorations in Urban Data Collection (2007)Does Urban Mobility Have a Daily Routine? Learning from the Aggregate Data of Mobile Networks (2010)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Principal Component Analysis on Spatial Data: An Overview (2012)A Coefficient of Agreement for Nominal Scales (1960)A Survey Method for Characterizing Daily Life Experience: The Day Reconstruction Method (2004)Ubiquitous Advertising: The Killer Application for the 21st Century (2010)Contextual conditional models for smartphone-based human mobility prediction (2012)Mining smartphone data for app usage prediction and recommendations: A survey (2017)Digital Footprinting: Uncovering Tourists with User-Generated Content (2008)When a city tells a story (2012)You are where you e-mail (2012)Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm (2015)Uncovering individual and collective human dynamics from mobile phone records (2008)Understanding individual human mobility patterns (2008)Computational Social Science (2009)Extracting Mobile Behavioral Patterns with the Distant N-Gram Topic Model (2012)A probabilistic approach to mining mobile phone data sequences (2013)Passive social sensing with smartphones: a systematic review (2022)The Massachusetts Institute of Technology (1999)Mining large-scale smartphone data for personality studies (2011)Measuring Large-Scale Social Networks with High Resolution (2014)Software or wetware? (2007)Easy on that trigger dad: a study of long term family photo retrieval (2009)Emotions beyond the laboratory: Theoretical fundaments, study design, and analytic strategies for advanced ambulatory assessment (2010)Inferring land use from mobile phone activity (2012)Analysis methods for extracting knowledge from large-scale WiFi monitoring to inform building facility planning (2014)Towards a Comparative Science of Cities: Using Mobile Traffic Records in New York, London, and Hong Kong (2014)Bridging the gap between physical location and online social networks (2010)Predictability of population displacement after the 2010 Haiti earthquake (2012)A survey of results on mobile phone datasets analysis (2015)
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References

  • 2006MyLifeBits516 cited
  • 2009Eigenbehaviors: identifying structure in routine504 cited
  • 2009Eigenbehaviors: identifying structure in routine439 cited
  • 2006Mobility Detection Using Everyday GSM Traces277 cited
  • 2009Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network262 cited
  • 2004Extracting places from traces of locations238 cited
  • 2011Extracting urban patterns from location-based social networks147 cited
  • 2006Farther Than You May Think: An Empirical Investigation of the Proximity of Users to Their Mobile Phones128 cited
  • 2009Eigenplaces: Segmenting Space through Digital Signatures115 cited
  • 2010Probabilistic Mining of Socio-Geographic Routines From Mobile Phone Data71 cited
  • 2011Discovering daily routines from Google Latitude with topic models49 cited
  • 2007Supporting Location-Aware Services for Mobile Users with the Whereabouts Diary30 cited
  • 2010Predicting human behaviour from selected mobile phone data points29 cited
  • 2008Daily Routine Classification from Mobile Phone Data29 cited
  • 2008Supporting location-aware services for mobile users with the whereabouts diary22 cited

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