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Interactive Visualization of Urban Areas of Interest: A Parameter-Free and Efficient Footprint Method

conference contribution
posted on 2024-11-03, 12:20 authored by Mingzhao Li, Zhifeng Bao, Farhana Choudhury, Timos Sellis
Understanding urban areas of interest (AOIs) is essential to decision making in various urban planning and exploration tasks. Such AOIs can be computed based on the geographic points that satisfy the user query. In this demo, we present an interactive visualization system of urban AOIs, supported by a parameter-free and efficient footprint method called AOI-shapes. Compared to state-of-the-art footprint methods, the proposed AOI-shapes (i) is parameter-free, (ii) is able to recognize multiple regions/outliers, (iii) can detect inner holes, and (iv) supports the incremental method. We demonstrate the effectiveness and efficiency of the proposed AOI-shapes based on a real-world real estate dataset in Australia. A preliminary version of the online demo can be accessed at http://aoishapes.com/.

Funding

Continuous and summarised search over evolving heterogeneous data

Australian Research Council

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Continuous intent tracking for virtual assistance using big contextual data

Australian Research Council

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History

Related Materials

  1. 1.
    DOI - Is published in 10.1145/3289600.3290612
  2. 2.
    ISBN - Is published in 9781450359405 (urn:isbn:9781450359405)

Start page

782

End page

785

Total pages

4

Outlet

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019

Name of conference

Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019

Publisher

ACM

Place published

New York, USA

Start date

2019-02-11

End date

2019-02-15

Language

English

Copyright

© 2019 the owner/author(s)

Former Identifier

2006090055

Esploro creation date

2020-06-22

Fedora creation date

2019-03-26

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