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Customer Segmentation through Path Reconstruction
This paper deals with the automatic classification of customers on the basis of their movements around a sports shop center. We start by collecting coordinates from customers while they visit the store. Consequently, any costumer’s path through the shop is formed by a list of coordinates, obtained w...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001414/ https://www.ncbi.nlm.nih.gov/pubmed/33809118 http://dx.doi.org/10.3390/s21062007 |
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author | Carbajal, Santiago García |
author_facet | Carbajal, Santiago García |
author_sort | Carbajal, Santiago García |
collection | PubMed |
description | This paper deals with the automatic classification of customers on the basis of their movements around a sports shop center. We start by collecting coordinates from customers while they visit the store. Consequently, any costumer’s path through the shop is formed by a list of coordinates, obtained with a frequency of one measurement per minute. A guess about the trajectory is constructed, and a number of parameters are calculated before performing a Clustering Process. As a result, we can identify several types of customers, and the dynamics of their behavior inside the shop. We can also monitor the state of the shop, identify different situations that appear during limited periods of time, and predict peaks in customer traffic. |
format | Online Article Text |
id | pubmed-8001414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80014142021-03-28 Customer Segmentation through Path Reconstruction Carbajal, Santiago García Sensors (Basel) Technical Note This paper deals with the automatic classification of customers on the basis of their movements around a sports shop center. We start by collecting coordinates from customers while they visit the store. Consequently, any costumer’s path through the shop is formed by a list of coordinates, obtained with a frequency of one measurement per minute. A guess about the trajectory is constructed, and a number of parameters are calculated before performing a Clustering Process. As a result, we can identify several types of customers, and the dynamics of their behavior inside the shop. We can also monitor the state of the shop, identify different situations that appear during limited periods of time, and predict peaks in customer traffic. MDPI 2021-03-12 /pmc/articles/PMC8001414/ /pubmed/33809118 http://dx.doi.org/10.3390/s21062007 Text en © 2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technical Note Carbajal, Santiago García Customer Segmentation through Path Reconstruction |
title | Customer Segmentation through Path Reconstruction |
title_full | Customer Segmentation through Path Reconstruction |
title_fullStr | Customer Segmentation through Path Reconstruction |
title_full_unstemmed | Customer Segmentation through Path Reconstruction |
title_short | Customer Segmentation through Path Reconstruction |
title_sort | customer segmentation through path reconstruction |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001414/ https://www.ncbi.nlm.nih.gov/pubmed/33809118 http://dx.doi.org/10.3390/s21062007 |
work_keys_str_mv | AT carbajalsantiagogarcia customersegmentationthroughpathreconstruction |