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    GeoTree: a data structure for constant time geospatial search enabling a real-time mix-adjusted median property price index


    Maguire, Phil (2020) GeoTree: a data structure for constant time geospatial search enabling a real-time mix-adjusted median property price index. International Journal of Intelligent Computing and Cybernetics. ISSN 1756-378X

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    Abstract

    A common problem appearing across the field of data science is k-NN (k-nearest neighbours), particularly within the context of Geographic Information Systems. In this article, we present a novel data structure, the GeoTree, which holds a collection of geohashes (string encodings of GPS co-ordinates). This enables a constant O (1) time search algorithm that returns a set of geohashes surrounding a given geohash in the GeoTree, representing the approximate k-nearest neighbours of that geohash. Furthermore, the GeoTree data structure retains an O (n) memory requirement. We apply the data structure to a property price index algorithm focused on price comparison with historical neighbouring sales, demonstrating an enhanced performance. The results show that this data structure allows for the development of a real-time property price index, and can be scaled to larger datasets with ease.

    Item Type: Article
    Additional Information: Cite as: Miller, R., Maguire, P. (2021). GeoTree: A Data Structure for Constant Time Geospatial Search Enabling a Real-Time Property Index. In: Arai, K. (eds) Intelligent Computing. Lecture Notes in Networks and Systems, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-030-80126-7_12
    Keywords: GeoTree; Geospatial; k-NN; Data structure; Price index;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 17473
    Identification Number: https://doi.org/10.1007/978-3-030-80126-7_12
    Depositing User: Phil Maguire
    Date Deposited: 31 Aug 2023 11:29
    Journal or Publication Title: International Journal of Intelligent Computing and Cybernetics
    Publisher: Springer Link
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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