Discovering Organized POI Groups in a city

Xu, Yanxia, Liu, Guanfeng, Yin, Hongzhi, Xu, Jiajie, Zheng, Kai and Zhao, Lei (2015). Discovering Organized POI Groups in a city. In: An Liu, Yoshiharu Ishikawa, Tieyun Qian, Sarana Nutanong and Muhammad Aamir Cheema, Database Systems for Advanced Applications DASFAA 2015. 20th International Conference on Database Systems for Advanced Applications (DASFAA), Hanoi, Vietnam, (223-226). 20-23 April 2015. doi:10.1007/978-3-319-22324-7_19

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Author Xu, Yanxia
Liu, Guanfeng
Yin, Hongzhi
Xu, Jiajie
Zheng, Kai
Zhao, Lei
Title of paper Discovering Organized POI Groups in a city
Conference name 20th International Conference on Database Systems for Advanced Applications (DASFAA)
Conference location Hanoi, Vietnam
Conference dates 20-23 April 2015
Proceedings title Database Systems for Advanced Applications DASFAA 2015   Check publisher's open access policy
Journal name Database Systems for Advanced Applications, Dasfaa 2015   Check publisher's open access policy
Series Lecture Notes in Computer Science
Place of Publication Heidelberg, Germany
Publisher Springer International Publishing
Publication Year 2015
Sub-type Fully published paper
DOI 10.1007/978-3-319-22324-7_19
Open Access Status Not Open Access
ISBN 9783319223230
ISSN 0302-9743
Editor An Liu
Yoshiharu Ishikawa
Tieyun Qian
Sarana Nutanong
Muhammad Aamir Cheema
Volume 9052
Start page 223
End page 226
Total pages 4
Collection year 2016
Language eng
Abstract/Summary With the development of urban modernization, a great number of hot spots, such as buildings, business streets and shopping malls, scatter over the city which have a great influence on people’s lives and modern civilization. All of these hot spots consist of a set of point of interests (POIs). In this paper, we propose a new concept, i.e., Organized POI Group (OPG) and present a method to find them out. In addition, we classify the OPGs as three categories: building, street and village, according to their features.
Keyword Urban computing
Organized POI groups
Spatio-textual similarity
Density-based clustering
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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