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From Foursquare to My Square: Learning Check-in Behavior from Multiple Sources
4 references·2 citing·24 second hop
From Foursquare to My Square: Learning Check-in Behavior from Multiple Sources (2021)From Foursquare to My Square: Learning Ch…The Mobile Data Challenge: Big Data for Mobile Computing Research (2012)The Mobile Data Challenge: Bi…Checking in or checked in (2012)Checking in or checked inBeen There, Done That: What Your Mobility Traces Reveal about Your Behavior (2012)Been There, Done That: What Y…Discovering human places of interest from multimodal mobile phone data (2010)Discovering human places of i…Spatiotemporal Structure Features of Network Check-in Activities of Urban Residents and Their Impacting Factors: A Case Study in Six Urban Districts of Beijing (2017)Spatiotemporal Structure Feat…Spatio-Temporal Modeling of Users' Check-ins in Location-Based Social Networks (2016)Spatio-Temporal Modeling of U…Understanding individual human mobility patterns (2008)Inferring friendship network structure by using mobile phone data (2009)Find me if you can (2010)Predicting future locations with hidden Markov models (2012)Measuring Large-Scale Social Networks with High Resolution (2014)A survey on deep learning for human mobility (2023)Using GPS to learn significant locations and predict movement across multiple users (2003)Learning transportation mode from raw gps data for geographic applications on the web (2008)Understanding mobility based on GPS data (2008)From big smartphone data to worldwide research: The Mobile Data Challenge (2013)Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis (2018)A Characterization of the COVID-19 Pandemic Impact on a Mobile Network Operator Traffic (2020)Computational Social Science (2009)Friendship and mobility (2011)Location Recommendation based on location-based social networks for Entertainment services (2015)Mobility Intention-Based Relationship Inference from Spatiotemporal Data (2017)An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks (2019)Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts (2016)Extracting urban patterns from location-based social networks (2011)When a city tells a story (2012)Inferring Urban Land Use Using Large-Scale Social Media Check-in Data (2014)Where Will You Go? Mobile Data Mining for Next Place Prediction (2013)Location choice with longitudinal WiFi data (2016)Mobile crowd location prediction with hybrid features using ensemble learning (2018)
this work references cited by second hop

References

  • 2012The Mobile Data Challenge: Big Data for Mobile Computing Research429 cited
  • 2010Discovering human places of interest from multimodal mobile phone data121 cited
  • 2012Been There, Done That: What Your Mobility Traces Reveal about Your Behavior42 cited
  • 2012Checking in or checked in23 cited

Cited by

  • 2017Spatiotemporal Structure Features of Network Check-in Activities of Urban Residents and Their Impacting Factors: A Case Study in Six Urban Districts of Beijing8 cited
  • 2016Spatio-Temporal Modeling of Users' Check-ins in Location-Based Social Networks6 cited

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