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The Study of Urban Residential’s Public Space Activeness Using Space-Centric Approach
6 references·1 citing·31 second hop
The Study of Urban Residential’s Public Space Activeness Using Space-Centric Approach (2021)The Study of Urban Residential’s Public S…Understanding Crowd Behaviors in a Social Event by Passive WiFi Sensing and Data Mining (2020)Understanding Crowd Behaviors…Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data (2020)Multiple-Perspective Clusteri…Understanding the Lifestyle of Older Population: Mobile Crowdsensing Approach (2018)Understanding the Lifestyle o…WiFi Tracking of Pedestrian Behavior (2017)WiFi Tracking of Pedestrian B…Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment (2015)Understanding Mobile Traffic …Participatory Bluetooth Scans Serving as Urban Crowd Probes (2014)Participatory Bluetooth Scans…Bus travel feature inference with small samples based on multi-clustering topic model over Internet of Things (2024)Bus travel feature inference …Reality mining: sensing complex social systems (2005)Discovering routines from large-scale human locations using probabilistic topic models (2011)The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities (2011)Quantitative evaluation of public spaces using crowd replication (2016)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)Private traits and attributes are predictable from digital records of human behavior (2013)Detecting Popular Temporal Modes in Population-scale Unlabelled Trajectory Data (2018)MAC (2019)Revealing Urban Dynamics by Learning Online and Offline Behaviours Together (2019)Human behavior and the principle of least effort (1949)Tracking unmodified smartphones using wi-fi monitors (2012)Leveraging proximity sensing to mine the behavior of museum visitors (2016)Identifying Movements in Noisy Crowd Analytics Data (2018)Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application (2019)PmA: A real-world system for people mobility monitoring and analysis based on Wi-Fi probes (2020)On Combining Crowdsourcing, Sensing and Open Data for an Accessible Smart City (2014)Uber Movement Data: A Proxy for Average One-way Commuting Times by Car (2020)Trip Purposes Mining From Mobile Signaling Data (2021)WiFi Fingerprint Clustering for Urban Mobility Analysis (2021)An Analysis of Visitors' Behavior in the Louvre Museum: A Study Using Bluetooth Data (2014)Analysis methods for extracting knowledge from large-scale WiFi monitoring to inform building facility planning (2014)Indoor Location Data for Tracking Human Behaviours: A Scoping Review (2022)Internet of Things Data Visualization for Business Intelligence (2022)Zooming into mobility to understand cities: A review of mobility-driven urban studies (2022)Urban computing with taxicabs (2011)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Clustering and Analysis of GPS Trajectory Data Using Distance-Based Features (2022)Optimization of bus stop placement for routes on uneven topography (2015)A multi-objective meta-heuristic approach for transit network design and frequency setting problem in a bus transit system (2019)IoT-Based Context-Aware Intelligent Public Transport System in a Metropolitan Area (2019)
this work references cited by second hop

References

  • 2015Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment151 cited
  • 2020Understanding Crowd Behaviors in a Social Event by Passive WiFi Sensing and Data Mining77 cited
  • 2018Understanding the Lifestyle of Older Population: Mobile Crowdsensing Approach42 cited
  • 2014Participatory Bluetooth Scans Serving as Urban Crowd Probes28 cited
  • 2017WiFi Tracking of Pedestrian Behavior27 cited
  • 2020Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data10 cited

Cited by

  • 2024Bus travel feature inference with small samples based on multi-clustering topic model over Internet of Things7 cited

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