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Urbanity: A System for Interactive Exploration of Urban Dynamics from Streaming Human Sensing Data

Published: 06 November 2017 Publication History

Abstract

With the urbanization process worldwide, modeling the dynamics of people's activities in urban environments has become a crucial socioeconomic task. We present Urbanity, a novel system that leverages geo-tagged social media streams for modeling urban dynamics. Urbanity automatically discovers the spatial and temporal hotspots where people's activities concentrate; and captures the cross-modal correlations among location, time, and text by jointly mapping different units into the same latent space. With Urbanity, the end users are able to use flexible query schemes to retrieve different resources (e.g., POIs, hotspots, hours, activities) that meet their needs. Furthermore, Urbanity can handle continuous streams to update the learned model, thus revealing up-to-date patterns of urban activities.

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Cited By

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  • (2020)User Group Analytics Survey and Research OpportunitiesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.291365132:10(2040-2059)Online publication date: 1-Oct-2020
  • (2019)Efficient User Guidance for Validating Participatory Sensing DataACM Transactions on Intelligent Systems and Technology10.1145/332616410:4(1-30)Online publication date: 17-Jul-2019
  • (2018)Human Factors in Data Science2018 IEEE 34th International Conference on Data Engineering (ICDE)10.1109/ICDE.2018.00009(1-12)Online publication date: Apr-2018

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  1. Urbanity: A System for Interactive Exploration of Urban Dynamics from Streaming Human Sensing Data

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    cover image ACM Conferences
    CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
    November 2017
    2604 pages
    ISBN:9781450349185
    DOI:10.1145/3132847
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 06 November 2017

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    Author Tags

    1. activity modeling
    2. multimodal embedding
    3. social media
    4. spatiotemporal data
    5. urban computing

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    View all
    • (2020)User Group Analytics Survey and Research OpportunitiesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.291365132:10(2040-2059)Online publication date: 1-Oct-2020
    • (2019)Efficient User Guidance for Validating Participatory Sensing DataACM Transactions on Intelligent Systems and Technology10.1145/332616410:4(1-30)Online publication date: 17-Jul-2019
    • (2018)Human Factors in Data Science2018 IEEE 34th International Conference on Data Engineering (ICDE)10.1109/ICDE.2018.00009(1-12)Online publication date: Apr-2018

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