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Context-aware multi-head self-attentional neural network model for next location prediction
16 references·6 citing·37 second hop
Context-aware multi-head self-attentional neural network model for next location prediction (2023)Context-aware multi-head self-attentional…A survey on deep learning for human mobility (2023)A survey on deep learning for…The universal visitation law of human mobility (2021)The universal visitation law …Location based services: ongoing evolution and research agenda (2018)Location based services: ongo…Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs (2018)Beyond Word2vec: An approach …A Survey of Location Prediction on Twitter (2018)A Survey of Location Predicti…Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn (2015)Everyday space–time geographi…Analysis of human mobility patterns from GPS trajectories and contextual information (2015)Analysis of human mobility pa…Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs (2014)Modeling User Activity Prefer…Discovering Urban Functional Zones Using Latent Activity Trajectories (2014)Discovering Urban Functional …Unravelling daily human mobility motifs (2013)Unravelling daily human mobil…Understanding metropolitan patterns of daily encounters (2013)Understanding metropolitan pa…Next place prediction using mobility Markov chains (2012)Next place prediction using m…Modelling the scaling properties of human mobility (2010)Modelling the scaling propert…Limits of Predictability in Human Mobility (2010)Limits of Predictability in H…Understanding individual human mobility patterns (2008)Understanding individual huma…Learning significant locations and predicting user movement with GPS (2003)Learning significant location…SILO: Semantic Integration for Location Prediction with Large Language Models (2025)SILO: Semantic Integration fo…Predicting urban mobility patterns with a LightGBM-enhanced gravity model: Insights from the Wuhan metropolitan area (2025)Predicting urban mobility pat…LingoTrip: Spatiotemporal context prompt driven large language model for individual trip prediction (2025)LingoTrip: Spatiotemporal con…Context-aware inverse reinforcement learning for modeling individuals’ daily activity schedules (2025)Context-aware inverse reinfor…Activity-aware urban area embedding with contrastive learning for intelligent transportation systems applications (2025)Activity-aware urban area emb…Evaluating geospatial context information for travel mode detection (2023)Evaluating geospatial context…Reality mining: sensing complex social systems (2005)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Returners and explorers dichotomy in human mobility (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Understanding mobility based on GPS data (2008)Predicting future locations with hidden Markov models (2012)Approaching the Limit of Predictability in Human Mobility (2013)Understanding Human Mobility from Twitter (2015)The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)A universal model for mobility and migration patterns (2012)Map projections: A working manual (1987)Discovering regions of different functions in a city using human mobility and POIs (2012)Methodologies for Cross-Domain Data Fusion: An Overview (2015)Regularity and Conformity (2015)The Livehoods Project: Utilizing Social Media to Understand the Dynamics of a City (2021)Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach (2021)Friendship and mobility (2011)Participatory Cultural Mapping Based on Collective Behavior Data in Location-Based Social Networks (2016)Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach (2019)Exploring Millions of Footprints in Location Sharing Services (2021)Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)The Museum Wearable: real-time sensor-driven understanding of visitors' interests for personalized visually-augmented museum experiences (2002)Discovering personally meaningful places (2007)Geographical information science (1992)Journal of Spatial Information Science (2011)Geospatial big data handling theory and methods: A review and research challenges (2015)A Large Scale, App-Based Behaviour Change Experiment Persuading Sustainable Mobility Patterns: Methods, Results and Lessons Learnt (2019)Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions (2021)Trackintel: An open-source Python library for human mobility analysis (2023)Growth in Cities (1992)The Spatial Economy (1999)Future directions in human mobility science (2023)Human mobility networks reveal increased segregation in large cities (2023)Resilience patterns of human mobility in response to extreme urban floods (2023)A survey of results on mobile phone datasets analysis (2015)Human mobility: Models and applications (2018)
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References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2010Limits of Predictability in Human Mobility3,230 cited
  • 2010Modelling the scaling properties of human mobility1,286 cited
  • 2014Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs857 cited
  • 2013Unravelling daily human mobility motifs584 cited
  • 2012Next place prediction using mobility Markov chains555 cited
  • 2021The universal visitation law of human mobility428 cited
  • 2014Discovering Urban Functional Zones Using Latent Activity Trajectories413 cited
  • 2003Learning significant locations and predicting user movement with GPS334 cited
  • 2018Location based services: ongoing evolution and research agenda317 cited
  • 2023A survey on deep learning for human mobility282 cited
  • 2015Analysis of human mobility patterns from GPS trajectories and contextual information275 cited
  • 2018Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs258 cited
  • 2018A Survey of Location Prediction on Twitter248 cited
  • 2013Understanding metropolitan patterns of daily encounters233 cited

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  • 2015Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn163 cited
  • Cited by

    • 2025LingoTrip: Spatiotemporal context prompt driven large language model for individual trip prediction16 cited
    • 2023Evaluating geospatial context information for travel mode detection11 cited
    • 2025Activity-aware urban area embedding with contrastive learning for intelligent transportation systems applications8 cited
    • 2025Predicting urban mobility patterns with a LightGBM-enhanced gravity model: Insights from the Wuhan metropolitan area6 cited
    • 2025Context-aware inverse reinforcement learning for modeling individuals’ daily activity schedules6 cited
    • 2025SILO: Semantic Integration for Location Prediction with Large Language Models5 cited