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Predicting Mobile Phone User Locations by Exploiting Collective Behavioral Patterns
5 references·8 citing·35 second hop
Predicting Mobile Phone User Locations by Exploiting Collective Behavioral Patterns (2012)Predicting Mobile Phone User Locations by…Friendship and mobility (2011)Friendship and mobilityLimits of Predictability in Human Mobility (2010)Limits of Predictability in H…Human mobility prediction based on individual and collective geographical preferences (2010)Human mobility prediction bas…Inferring friendship network structure by using mobile phone data (2009)Inferring friendship network …Evolution of mobile location-based services (2003)Evolution of mobile location-…Decomposition of travel time expenditure through individual mobility trajectories based on mobile phone signaling data (2023)Decomposition of travel time …Spatial–temporal visualization of city-wide crowd movement (2016)Spatial–temporal visualizatio…Visualizing the time-varying crowd mobility (2015)Visualizing the time-varying …Multi-hop Mobility Prediction (2015)Multi-hop Mobility PredictionHybrid Markov Location Prediction Algorithm Based on Dynamic Social Ties (2015)Hybrid Markov Location Predic…Probabilistic Inference of Unknown Locations (2014)Probabilistic Inference of Un…Where is the Largest Market: Ranking Areas by Popularity from Location Based Social Networks (2013)Where is the Largest Market: …MPaaS: Mobility prediction as a service in telecom cloud (2013)MPaaS: Mobility prediction as…Reality mining: sensing complex social systems (2005)The origin of bursts and heavy tails in human dynamics (2005)Understanding individual human mobility patterns (2008)Modelling the scaling properties of human mobility (2010)A universal model for mobility and migration patterns (2012)Find me if you can (2010)Predicting future locations with hidden Markov models (2012)Modeling location-based social network data with area attraction and neighborhood competition (2018)PACELA (2018)Birds of a Feather: Homophily in Social Networks (2001)Power-Law Distributions in Empirical Data (2009)Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs (2014)Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts (2016)DeepMove (2018)Power-law distributions in empirical data (2018)Psychological status of the script concept. (1981)Computational Social Science (2009)Dynamics of Dyads in Social Networks: Assortative, Relational, and Proximity Mechanisms (2010)Human mobility: Models and applications (2018)Predestination: Inferring Destinations from Partial Trajectories (2006)Mining User Mobility Features for Next Place Prediction in Location-Based Services (2012)The use of time : Daily activities of urban and suburban populations in twelve countries (1972)The future mobility of the world population (2000)TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets (2004)A generative adversarial network for inferring age attributes in subway based on automatic fare collection and point of interest data (2024)A Transport Mode Detection Framework Based on Mobile Phone Signaling Data Combined with Bus GPS Data (2024)Unraveling metro mobility patterns in China: A multi-city comparative study using travel motifs and entropy analysis (2024)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)From Value Chain to Value Network: (2006)The Role of Push-Pull Technology in Privacy Calculus: The Case of Location-Based Services (2009)Why smartphone advertising attracts customers: A model of Web advertising, flow, and personalization (2014)Visualization and Assessment of the Effect of Roadworks on Traffic Congestion Using AVL Data of Public Transit (2022)Visualizing population mobility from spatiotemporally aggregated mobile phone data via a 3D gradient approach (2022)
this work references cited by second hop

References

  • 2010Limits of Predictability in Human Mobility3,230 cited
  • 2011Friendship and mobility2,912 cited
  • 2009Inferring friendship network structure by using mobile phone data1,858 cited
  • 2003Evolution of mobile location-based services454 cited
  • 2010Human mobility prediction based on individual and collective geographical preferences133 cited

Cited by

  • 2013MPaaS: Mobility prediction as a service in telecom cloud21 cited
  • 2016Spatial–temporal visualization of city-wide crowd movement21 cited
  • 2015Multi-hop Mobility Prediction18 cited
  • 2013Where is the Largest Market: Ranking Areas by Popularity from Location Based Social Networks14 cited
  • 2023Decomposition of travel time expenditure through individual mobility trajectories based on mobile phone signaling data9 cited
  • 2015Visualizing the time-varying crowd mobility8 cited
  • 2014Probabilistic Inference of Unknown Locations6 cited
  • 2015Hybrid Markov Location Prediction Algorithm Based on Dynamic Social Ties4 cited

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