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Eric Hsueh-Chan Lu and You-Ru Lin
With the rise in the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), abundant trajectory data have made research on location prediction more popular. The check-in data shared through LBSN hide information related to lif...
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Sumet Darapisut, Komate Amphawan, Nutthanon Leelathakul and Sunisa Rimcharoen
Location-based recommender systems (LBRSs) have exhibited significant potential in providing personalized recommendations based on the user?s geographic location and contextual factors such as time, personal preference, and location categories. However, ...
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Xinyi Lai and Chao Gao
The spatiotemporal patterns of residential and supporting service facilities are critical to effective urban planning. However, with growing urban sprawl and congestion, the spatial distribution patterns and evolutionary characteristics of these areas sh...
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Huili Zhang, Xiaowen Zhou, Huan Li, Ge Zhu and Hongwei Li
This study is oriented towards machine autonomous mapping and the need to improve the efficiency of map point symbol recognition and configuration. Therefore, an intelligent recognition method for point symbols was developed using the You Only Look Once ...
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Raymond Low, Zeynep Duygu Tekler and Lynette Cheah
Point of interest (POI) data serves as a valuable source of semantic information for places of interest and has many geospatial applications in real estate, transportation, and urban planning. With the availability of different data sources, POI conflati...
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Jincheng Wang, Qunqi Wu, Zilin Chen, Yilong Ren and Yaqun Gao
Ridesplitting, a form of ridesourcing in which riders with similar origins and destinations are matched, is an effective mode of sustainable transportation. In recently years, ridesplitting has spread rapidly worldwide and plays an increasingly important...
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Lih Wei Yeow, Raymond Low, Yu Xiang Tan and Lynette Cheah
Point-of-interest (POI) data from map sources are increasingly used in a wide range of applications, including real estate, land use, and transport planning. However, uncertainties in data quality arise from the fact that some of this data are crowdsourc...
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Chengming Li, Li Liu, Zhaoxin Dai and Xiaoli Liu
Point of interest (POI) matching is critical but is the most technically difficult part of multi-source POI fusion. The accurate matching of POIs from different sources is important for the effective reuse of POI data. However, the existing research on P...
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Mateusz Piech, Aleksander Smywinski-Pohl, Robert Marcjan and Leszek Siwik
Complementing information about particular points, places, or institutions, i.e., so-called Points of Interest (POIs) can be achieved by matching data from the growing number of geospatial databases; these include Foursquare, OpenStreetMap, Yelp, and Fac...
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