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A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization
4 references·3 citing·26 second hop
A Framework for Simplifying Trip Data into Networks via Coupled Matrix Factorization (2015)A Framework for Simplifying Trip Data int…Learning to rank for spatiotemporal search (2013)Learning to rank for spatiote…Mobility data mining (2010)Mobility data miningMobility, Data Mining and Privacy: Geographic Knowledge Discovery (2008)Mobility, Data Mining and Pri…Predestination: Inferring Destinations from Partial Trajectories (2006)Predestination: Inferring Des…Tensor Decomposition for Spatiotemporal Mobility Pattern Learning with Mobile Phone Data (2024)Tensor Decomposition for Spat…Mining Regional Mobility Patterns for Urban Dynamic Analytics (2019)Mining Regional Mobility Patt…Joint Mobility Pattern Mining with Urban Region Partitions (2018)Joint Mobility Pattern Mining…Using GPS to learn significant locations and predict movement across multiple users (2003)Understanding individual human mobility patterns (2008)You are where you tweet (2010)CEPR (2015)How where is when? On the regional variability and resolution of geosocial temporal signatures for points of interest (2015)Mobile Big Data: The Fuel for Data-Driven Wireless (2017)Summary of Travel Trends 2001 National Household Travel Survey (2005)Learning and inferring transportation routines (2007)Mining Individual Life Pattern Based on Location History (2009)Travel route recommendation using geotags in photo sharing sites (2010)NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems (2011)Urban computing with taxicabs (2011)Discovering regions of different functions in a city using human mobility and POIs (2012)Next place prediction using mobility Markov chains (2012)Mining Mobility Patterns with Trip-Based Traffic Analysis Zones: A Deep Feature Embedding Approach (2019)Characterizing Human Mobility Patterns During COVID-19 using Cellular Network Data (2021)Uncovering mobility typologies of territorial zones based on Floating Car Data mining (2021)Revealing travel patterns and city structure with taxi trip data (2015)The path most traveled: Travel demand estimation using big data resources (2015)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)Unravelling daily human mobility motifs (2013)Identifying urban spatial clusters via flow dynamics: a coupled tensor-based method (2025)From social data mining to forecasting socio-economic crises (2011)Methods for deriving and calibrating privacy-preserving heat maps from mobile sports tracking application data (2015)Big Data for transportation and mobility: recent advances, trends and challenges (2018)
this work references cited by second hop

References

  • 2006Predestination: Inferring Destinations from Partial Trajectories464 cited
  • 2008Mobility, Data Mining and Privacy: Geographic Knowledge Discovery195 cited
  • 2013Learning to rank for spatiotemporal search104 cited
  • 2010Mobility data mining12 cited

Cited by

  • 2019Mining Regional Mobility Patterns for Urban Dynamic Analytics8 cited
  • 2018Joint Mobility Pattern Mining with Urban Region Partitions7 cited
  • 2024Tensor Decomposition for Spatiotemporal Mobility Pattern Learning with Mobile Phone Data5 cited

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