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Understanding human movement semantics
8 references·2 citing·32 second hop
Understanding human movement semantics (2012)Understanding human movement semanticsModeling people's place naming preferences in location sharing (2010)Modeling people's place namin…Human mobility prediction based on individual and collective geographical preferences (2010)Human mobility prediction bas…Extracting human mobility patterns from GPS-based traces (2010)Extracting human mobility pat…Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data (2010)Activity-Aware Map: Identifyi…Measuring serendipity (2009)Measuring serendipityUnderstanding mobility based on GPS data (2008)Understanding mobility based …Understanding individual human mobility patterns (2008)Understanding individual huma…The scaling laws of human travel (2006)The scaling laws of human tra…CellRep: Usage Representativeness Modeling and Correction Based on Multiple City-Scale Cellular Networks (2020)CellRep: Usage Representative…GeoEcho: Inferring User Interests from Geotag Reports in Network Traffic (2014)GeoEcho: Inferring User Inter…Reality mining: sensing complex social systems (2005)Limits of Predictability in Human Mobility (2010)Correlating mobile phone usage and travel behavior – A case study of Harbin, China (2011)Intra-urban human mobility patterns: An urban morphology perspective (2011)Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach (2015)Friendship and mobility (2011)The origin of bursts and heavy tails in human dynamics (2005)A universal model for mobility and migration patterns (2012)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)You are where you eat: Foursquare checkins as indicators of human mobility and behaviour (2012)How many places do you visit a day? (2013)A Data Driven Approach to Match Demand and Supply for Public Transport Planning (2020)An architecture for privacy-sensitive ubiquitous computing (2004)Location disclosure to social relations (2005)Rethinking location sharing (2010)Are you close with me? are you nearby? (2011)Modeling Users’ Mobile App Privacy Preferences: Restoring Usability in a Sea of Permission Settings (2018)Learning and inferring transportation routines (2007)Next place prediction using mobility Markov chains (2012)Understanding Human Mobility from Twitter (2015)Human mobility modeling at metropolitan scales (2012)Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment (2016)Human mobility: Models and applications (2018)Characterizing Human Mobility Patterns During COVID-19 using Cellular Network Data (2021)Mover (2021)Are call detail records biased for sampling human mobility? (2012)A Tale of Ten Cities: Characterizing Signatures of Mobile Traffic in Urban Areas (2016)Understanding the impact of personality traits on mobile app adoption – Insights from a large-scale field study (2016)Using Google Location History data to quantify fine-scale human mobility (2018)A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction (2020)Future directions in human mobility science (2023)
this work references cited by second hop

References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2006The scaling laws of human travel2,207 cited
  • 2008Understanding mobility based on GPS data1,131 cited
  • 2010Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data280 cited
  • 2009Measuring serendipity170 cited
  • 2010Human mobility prediction based on individual and collective geographical preferences133 cited
  • 2010Modeling people's place naming preferences in location sharing64 cited
  • 2010Extracting human mobility patterns from GPS-based traces31 cited

Cited by

  • 2020CellRep: Usage Representativeness Modeling and Correction Based on Multiple City-Scale Cellular Networks7 cited
  • 2014GeoEcho: Inferring User Interests from Geotag Reports in Network Traffic3 cited

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