Administrative Regions Discovery Based on Human Mobility Patterns and Spatio-Temporal Clustering

被引:0
作者
Nunez-del-Prado-Cortez, Miguel [1 ]
Alatrista-Salas, Hugo [1 ]
机构
[1] Univ Pacifico, Ave Salaverry 2020, Lima, Peru
来源
PROCEEDINGS 2016 IEEE 13TH INTERNATIONAL CONFERENCE ON MOBILE AD HOC AND SENSOR SYSTEMS (MASS 2016) | 2016年
关键词
Mobility model; Mobility Markov chain; administrative region; clustering; region interactions;
D O I
10.1109/MASS.2016.58
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Currently, the understanding of the human mobility is an important challenge that has a large number of applications, especially in the study of a nations ability to thrive economically and socially. Some works have shown that, it is possible to observe developed and developing countries reviewing their administrative regions borders, in order to reduce costs, or to solve ethnic claims and/or independence movements. In this context, the present work leverages mobile phone data to analyze human mobility patterns. Specifically, we propose a new method to detect administrative regions and paths of interaction between regions, both relying on subscribers mobility patterns extracted from Call Detail Records (CDR). Thus, our method offers a different point of view to redefine administrative boundaries.
引用
收藏
页码:65 / 74
页数:10
相关论文
共 50 条
[1]   Discovery of Patterns in Spatio-Temporal Data Using Clustering Techniques [J].
Aryal, Amar Mani ;
Wang, Sujing .
2017 2ND INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC 2017), 2017, :990-995
[2]   Discovery of Spatio-Temporal Patterns from Location Based Social Networks [J].
Bejar, Javier ;
Alvarez, Sergio ;
Garcia, Dario ;
Gomez, Ignasi ;
Oliva, Luis ;
Tejeda, Arturo ;
Vazquez-Salceda, Javier .
ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT: RECENT ADVANCES AND APPLICATIONS, 2014, 269 :126-135
[3]   Discovery of spatio-temporal patterns from location-based social networks [J].
Bejar, J. ;
Alvarez, S. ;
Garcia, D. ;
Gomez, I. ;
Oliva, L. ;
Tejeda, A. ;
Vazquez-Salceda, J. .
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2016, 28 (1-2) :313-329
[4]   Mobility Graphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering [J].
von Landesberger, Tatiana ;
Brodkorb, Felix ;
Roskosch, Philipp ;
Andrienko, Natalia ;
Andrienko, Gennady ;
Kerren, Andreas .
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2016, 22 (01) :11-20
[5]   Spatio-Temporal Clustering of Road Obstacles [J].
Kreibich, Julian ;
Kuppel, Mario .
2022 INTERNATIONAL CONFERENCE ON CONNECTED VEHICLE AND EXPO, ICCVE, 2022,
[6]   Development and validation of OPTICS based spatio-temporal clustering technique [J].
Agrawal, K. P. ;
Garg, Sanjay ;
Sharma, Shashikant ;
Patel, Pinkal .
INFORMATION SCIENCES, 2016, 369 :388-401
[7]   CorClustST-Correlation-based clustering of big spatio-temporal datasets [J].
Huesch, Marc ;
Schyska, Bruno U. ;
von Bremen, Lueder .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2020, 110 :610-619
[8]   RetweetPatterns: detection of spatio-temporal patterns of retweets [J].
Rodrigues, Tomy ;
Cunha, Tiago ;
Ienco, Dino ;
Poncelet, Pascal ;
Soares, Carlos .
NEW ADVANCES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 1, 2016, 444 :879-888
[9]   TweeProfiles: Detection of Spatio-temporal Patterns on Twitter [J].
Cunha, Tiago ;
Soares, Carlos ;
Rodrigues, Eduarda Mendes .
ADVANCED DATA MINING AND APPLICATIONS, ADMA 2014, 2014, 8933 :123-136
[10]   Contextual location prediction using spatio-temporal clustering [J].
Guessoum, Djamel ;
Miraoui, Moeiz ;
Tadj, Chakib .
INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS, 2016, 12 (03) :290-309