PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest

Rafael Christófano, Wilson Marcílio Júnior, Danilo Eler

2021

Abstract

Understanding how commercial and social activities and points of interest are located in a city is essential to plan efficient cities in smart mobility. Over the years, the growth of data sources from distinct online social networks has enabled new perspectives to applications that provide mechanisms to aid in comprehension of how people displaces between different regions within a city. To support enterprises and governments better understand and compare distinct regions of a city, this work proposes a web application called PlaceProfile to perform visual profiling of city areas based on iconographic visualization and to label areas based on clustering algorithms. The visualization results are overlayered on Google Maps to enrich the map layout and aid analyst in understanding region profiling at a glance. Besides, PlaceProfile coordinates a radar chart with areas selected by the user to enable detailed inspection of the frequency of categories of points of interest (POIs). This linked views approach also supports clustering algorithms’ explainability by providing inspections of the attributes used to compute similarities. We employed the proposed approach in a case study in the São Paulo city, Brazil.

Paper Citation

in Harvard Style

Christófano R., Marcílio Júnior W. and Eler D. (2021). PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 506-514. DOI: 10.5220/0010453405060514

in Bibtex Style

@conference{iceis21,
author={Rafael Christófano and Wilson Marcílio Júnior and Danilo Eler},
title={PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={506-514},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010453405060514},
isbn={978-989-758-509-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest
SN - 978-989-758-509-8
AU - Christófano R.
AU - Marcílio Júnior W.
AU - Eler D.
PY - 2021
SP - 506
EP - 514
DO - 10.5220/0010453405060514