StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets

Bike sharing systems (BSS) have emerged as an alternative and environmentally friendly transportation tool that provides short-term bike rental to city residents for their close proximity transportation purposes or sports activities. With the emergence and widespread usage of BSS, BSS operators star...

Full description

Saved in:
Bibliographic Details
Main Author: Ahmet Şakir Dokuz
Format: Article
Language:English
Published: Sakarya University 2021-02-01
Series:Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
Subjects:
Online Access:https://dergipark.org.tr/tr/download/article-file/1277635
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850134578871664640
author Ahmet Şakir Dokuz
author_facet Ahmet Şakir Dokuz
author_sort Ahmet Şakir Dokuz
collection DOAJ
description Bike sharing systems (BSS) have emerged as an alternative and environmentally friendly transportation tool that provides short-term bike rental to city residents for their close proximity transportation purposes or sports activities. With the emergence and widespread usage of BSS, BSS operators started collecting bike user-related datasets to benefit from it and to increase service quality. Many application areas are present which use BSS big datasets, such as behavioral analyses, urban pattern discovery, and network analysis of bike stations. A bike station network can be defined as a network where bike stations are nodes and the bike trips of users from a station to another station as edges. The extraction of bike station network provides information about which stations are central, which stations have more in- or out-flows, and which regions of the cities are actively used by bike users. However, the extraction of bike station networks is challenging due to the complexity and different characteristics of bike stations, the requirement of new algorithms and new visualization techniques, and the issues related to efficient handling BSS big datasets. In this study, the concept of bike station network extraction in terms of top-n correlated stations is proposed. In particular, the extraction of a bike station network from BSS big datasets are defined and a new algorithm is proposed for extraction of bike station network, and also a new visualization approach that uses common visualization tools is utilized to represent bike station network on a map which would provide more information than a network without a background information. The proposed algorithm and visualization technique are evaluated using one year BSS big dataset. Experimental results show that the proposed algorithm could successfully extract top-n correlated bike station networks and utilized visualization technique is beneficial.
format Article
id doaj-art-864f8bf5cc2a427d93ff090198a1d58b
institution OA Journals
issn 2147-835X
language English
publishDate 2021-02-01
publisher Sakarya University
record_format Article
series Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
spelling doaj-art-864f8bf5cc2a427d93ff090198a1d58b2025-08-20T02:31:40ZengSakarya UniversitySakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi2147-835X2021-02-0125127528728StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big DatasetsAhmet Şakir Dokuz0https://orcid.org/0000-0002-1775-0954NİĞDE ÖMER HALİSDEMİR ÜNİVERSİTESİBike sharing systems (BSS) have emerged as an alternative and environmentally friendly transportation tool that provides short-term bike rental to city residents for their close proximity transportation purposes or sports activities. With the emergence and widespread usage of BSS, BSS operators started collecting bike user-related datasets to benefit from it and to increase service quality. Many application areas are present which use BSS big datasets, such as behavioral analyses, urban pattern discovery, and network analysis of bike stations. A bike station network can be defined as a network where bike stations are nodes and the bike trips of users from a station to another station as edges. The extraction of bike station network provides information about which stations are central, which stations have more in- or out-flows, and which regions of the cities are actively used by bike users. However, the extraction of bike station networks is challenging due to the complexity and different characteristics of bike stations, the requirement of new algorithms and new visualization techniques, and the issues related to efficient handling BSS big datasets. In this study, the concept of bike station network extraction in terms of top-n correlated stations is proposed. In particular, the extraction of a bike station network from BSS big datasets are defined and a new algorithm is proposed for extraction of bike station network, and also a new visualization approach that uses common visualization tools is utilized to represent bike station network on a map which would provide more information than a network without a background information. The proposed algorithm and visualization technique are evaluated using one year BSS big dataset. Experimental results show that the proposed algorithm could successfully extract top-n correlated bike station networks and utilized visualization technique is beneficial.https://dergipark.org.tr/tr/download/article-file/1277635: top-n correlated bike stationsnetwork visualizationnetwork data miningbss big data mining
spellingShingle Ahmet Şakir Dokuz
StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
: top-n correlated bike stations
network visualization
network data mining
bss big data mining
title StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets
title_full StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets
title_fullStr StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets
title_full_unstemmed StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets
title_short StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets
title_sort stationnet an algorithm for the extraction and visualization of top n correlated bike stations in bike sharing systems big datasets
topic : top-n correlated bike stations
network visualization
network data mining
bss big data mining
url https://dergipark.org.tr/tr/download/article-file/1277635
work_keys_str_mv AT ahmetsakirdokuz stationnetanalgorithmfortheextractionandvisualizationoftopncorrelatedbikestationsinbikesharingsystemsbigdatasets