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@article{bb198103,
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@article{bb198105,
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@article{bb198106,
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        TITLE = "Monitoring Rural Water Points in Tanzania with Mobile Phones:
The Evolution of the SEMA App",
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@article{bb198107,
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@article{bb198108,
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with empirical and experimental data",
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@article{bb198110,
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Mobile Phone Big Data Mining",
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for trip mode prediction using mobile phone data",
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@article{bb198117,
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@article{bb198118,
        AUTHOR = "Gao, Z.Q. and Liu, D.W. and Huang, K. and Huang, Y.",
        TITLE = "Context-Aware Human Activity and Smartphone Position-Mining with
Motion Sensors",
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@article{bb198119,
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Emphasis on Intra-Zonal Trips",
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@article{bb198120,
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extracts from cellphone activity data",
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@article{bb198121,
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Phone Data: How Commuting Relates to Congestion",
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@article{bb198122,
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Methods and GPS Traces from Smartphone",
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@article{bb198123,
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@article{bb198124,
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@article{bb198125,
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@article{bb198126,
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@article{bb198127,
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@article{bb198128,
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Similarity Measure Based on Smart Card Data",
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@article{bb198129,
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Scales Using Mobile Phone Data",
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@article{bb198130,
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Phone Network Data",
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@article{bb198131,
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@article{bb198132,
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Smartphone Travel Survey",
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@article{bb198133,
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        TITLE = "Fine-Scale Dasymetric Population Mapping with Mobile Phone and
Building Use Data Based on Grid Voronoi Method",
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@article{bb198134,
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@article{bb198135,
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@article{bb198136,
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Registration Identification of Vehicles",
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@article{bb198137,
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Electronic Registration Identification of Vehicles",
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@article{bb198138,
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@article{bb198139,
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        TITLE = "Exploring the Potential of Twitter to Understand Traffic Events and
Their Locations in Greater Mumbai, India",
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@article{bb198140,
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Styria, Austria",
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@article{bb198141,
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Driving Event Detection Using Smartphones",
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@article{bb198143,
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Aggregated Cell Phone Data and Open Source GIS Tool",
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        NUMBER = "6",
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@article{bb198145,
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A Case Study in Beijing, China",
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@article{bb198146,
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        NUMBER = "6",
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@article{bb198147,
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        TITLE = "Phone-vehicle trajectory matching framework based on ALPR and
cellular signalling data",
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@article{bb198148,
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@article{bb198149,
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@article{bb198150,
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for Resilient and Safe Transportation Systems",
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Mobile Phone Signaling Data",
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Mode Detection Using Multimodal Sensors Integrated in Smartphones",
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China",
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of Spatial Interaction Networks Constructed from Human Communication
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@article{bb198159,
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@article{bb198160,
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on Smartphone Sensors",
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Learning for Cellular Traffic and Its Application in Urban Computing",
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@article{bb198162,
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Anonymized Mobile Communication Data",
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Using Cellular Data",
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With Overlapping Bluetooth Scanning Zones",
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Uncovering Urban Spatial Interaction Using Mobile-Phone Data",
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and Emission Assessments: An Agent-Based Approach",
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@article{bb198168,
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        TITLE = "A Survey on the Advancement of Travel Time Estimation Using Mobile
Phone Network Data",
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Spatiotemporal Characteristics Using Cellular Signaling Data",
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A Pattern-Based Approach",
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Trip Extraction, and Travel Mode Detection",
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@inproceedings{bb198193,
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