Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies

Location plays a very important role in geomarketing. Location tells where the customers are, identifies something in the surrounding area or solves problems regarding the location of a new outlet. However, in an urban area, the locations have a vertical component due to high-rise and multilevel bui...

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Main Authors: Azri, Suhaibah, Ujang, Uznir, Abdul Rahman, Alias
Format: Article
Published: Elsevier B. V. 2020
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Online Access:http://eprints.utm.my/id/eprint/87135/
http://dx.doi.org/10.1016/j.isprsjprs.2020.01.022
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spelling my.utm.871352020-10-31T12:23:45Z http://eprints.utm.my/id/eprint/87135/ Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies Azri, Suhaibah Ujang, Uznir Abdul Rahman, Alias NA Architecture Location plays a very important role in geomarketing. Location tells where the customers are, identifies something in the surrounding area or solves problems regarding the location of a new outlet. However, in an urban area, the locations have a vertical component due to high-rise and multilevel buildings. This situation requires a new approach that can handle three-dimensional data for location analysis. In this research, a novel 3D data structure is introduced to manage and constellate locations in three-dimensional space. The data structure is designed based on a group of classifications and clusters, and supplemented with the additional element of nearest-neighbour information. The locations are analysed to determine a geomarketing strategy by using several methods, such as single-nearest-neighbour, k-nearest-neighbour (kNN) and reverse-k-nearest-neighbour (RkNN) analyses. These analyses are performed based on encoded neighbour information of the Voronoi diagram that is extracted from the data structure. From the results, various tasks pertaining to geomarketing strategy can be carried out, such as identifying nearby competitors, locating target customers for marketing purposes and analysing the impact of opening a new outlet on competitors. Additionally, the proposed method is tested for its ability to handle large amounts of geomarketing data in terms of its efficiency in time retrieval and storage. The data structure is compared with 3D R-Tree to analyse its performance and efficiency. 3D R-Tree is chosen because it is the most commonly used structure in spatial databases. The test demonstrates that the proposed method requires the least amount of Input/Output than 3D R-Tree. The performance of the data structure is also evaluated; the results indicate that it is outperforms it competitors by responding 60–80% faster to query operations. Elsevier B. V. 2020-04 Article PeerReviewed Azri, Suhaibah and Ujang, Uznir and Abdul Rahman, Alias (2020) Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies. ISPRS Journal of Photogrammetry and Remote Sensing, 162 . pp. 1-16. ISSN 0924-2716 http://dx.doi.org/10.1016/j.isprsjprs.2020.01.022
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic NA Architecture
spellingShingle NA Architecture
Azri, Suhaibah
Ujang, Uznir
Abdul Rahman, Alias
Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies
description Location plays a very important role in geomarketing. Location tells where the customers are, identifies something in the surrounding area or solves problems regarding the location of a new outlet. However, in an urban area, the locations have a vertical component due to high-rise and multilevel buildings. This situation requires a new approach that can handle three-dimensional data for location analysis. In this research, a novel 3D data structure is introduced to manage and constellate locations in three-dimensional space. The data structure is designed based on a group of classifications and clusters, and supplemented with the additional element of nearest-neighbour information. The locations are analysed to determine a geomarketing strategy by using several methods, such as single-nearest-neighbour, k-nearest-neighbour (kNN) and reverse-k-nearest-neighbour (RkNN) analyses. These analyses are performed based on encoded neighbour information of the Voronoi diagram that is extracted from the data structure. From the results, various tasks pertaining to geomarketing strategy can be carried out, such as identifying nearby competitors, locating target customers for marketing purposes and analysing the impact of opening a new outlet on competitors. Additionally, the proposed method is tested for its ability to handle large amounts of geomarketing data in terms of its efficiency in time retrieval and storage. The data structure is compared with 3D R-Tree to analyse its performance and efficiency. 3D R-Tree is chosen because it is the most commonly used structure in spatial databases. The test demonstrates that the proposed method requires the least amount of Input/Output than 3D R-Tree. The performance of the data structure is also evaluated; the results indicate that it is outperforms it competitors by responding 60–80% faster to query operations.
format Article
author Azri, Suhaibah
Ujang, Uznir
Abdul Rahman, Alias
author_facet Azri, Suhaibah
Ujang, Uznir
Abdul Rahman, Alias
author_sort Azri, Suhaibah
title Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies
title_short Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies
title_full Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies
title_fullStr Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies
title_full_unstemmed Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies
title_sort voronoi classified and clustered data constellation: a new 3d data structure for geomarketing strategies
publisher Elsevier B. V.
publishDate 2020
url http://eprints.utm.my/id/eprint/87135/
http://dx.doi.org/10.1016/j.isprsjprs.2020.01.022
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score 13.211869