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Time-series Stay Frequency for Multi-City Next Location Prediction using Multiple BERTs
8 references·0 citing·29 second hop
Time-series Stay Frequency for Multi-City Next Location Prediction using Multiple BERTs (2024)Time-series Stay Frequency for Multi-City…YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories (2024)YJMob100K: City-scale and lon…Human Mobility Prediction Challenge: Next Location Prediction using Spatiotemporal BERT (2023)Human Mobility Prediction Cha…GeoFormer: Predicting Human Mobility using Generative Pre-trained Transformer (GPT) (2023)GeoFormer: Predicting Human M…Mobile phone location data for disasters: A review from natural hazards and epidemics (2022)Mobile phone location data fo…Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts (2016)Predicting the Next Location:…Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Activity-Based Human Mobility…Next place prediction using mobility Markov chains (2012)Next place prediction using m…Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Mobile Landscapes: Using Loca…Understanding mobility based on GPS data (2008)Limits of Predictability in Human Mobility (2010)Predicting future locations with hidden Markov models (2012)Approaching the Limit of Predictability in Human Mobility (2013)Understanding Human Mobility from Twitter (2015)Me++ (2003)Me++: The Cyborg Self and the Networked City (2003)Dynamic population mapping using mobile phone data (2014)Human mobility: Models and applications (2018)Friendship and mobility (2011)POI2Vec: Geographical Latent Representation for Predicting Future Visitors (2017)DeepMove (2018)Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States! (2020)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Understanding individual human mobility patterns (2008)Travel and the Built Environment (2010)On data processing required to derive mobility patterns from passively-generated mobile phone data (2017)Human mobility and socioeconomic status: Analysis of Singapore and Boston (2018)Measuring inequality in community resilience to natural disasters using large-scale mobility data (2021)A Population-Based Study (2009)Spatial structure of city population growth (2022)Leveraging machine learning algorithms for improved disaster preparedness and response through accurate weather pattern and natural disaster prediction (2023)A survey of results on mobile phone datasets analysis (2015)Enhancing human mobility research with open and standardized datasets (2024)Cross-city-aware Spatiotemporal BERT (2024)Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility Prediction (2024)Agentic Large Language Models for Generating Large-Scale Urban Daily Activity Patterns (2024)Learning Daily Human Mobility with a Transformer-Based Model (2024)Model of Sustainable Household Mobility in Multi-Modal Transportation Networks (2024)
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References

  • 2016Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts1,014 cited
  • 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis865 cited
  • 2012Next place prediction using mobility Markov chains555 cited
  • 2016Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore472 cited
  • 2022Mobile phone location data for disasters: A review from natural hazards and epidemics163 cited
  • 2024YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories68 cited
  • 2023Human Mobility Prediction Challenge: Next Location Prediction using Spatiotemporal BERT22 cited
  • 2023GeoFormer: Predicting Human Mobility using Generative Pre-trained Transformer (GPT)21 cited

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