Efficient sampling methods for characterizing POIs on maps based on road networks

With the rapid development of location-based services, a particularly important aspect of start-up marketing research is to explore and characterize points of interest (PoIs) such as restaurants and hotels on maps. However, due to the lack of direct access to PoI databases, it is necessary to rely o...

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Bibliographic Details
Published in:Frontiers of Computer Science 2018-06, Vol.12 (3), p.582-592
Main Authors: ZHOU, Ziting, ZHAO, Pengpeng, SHENG, Victor S., XU, Jiajie, LI, Zhixu, WU, Jian, CUI, Zhiming
Format: Article
Language:English
Subjects:
aggregate statistical estimation
Computer Science
Efficiency
Hotels & motels
Location based services
Mathematical analysis
Methods
Queries
Research Article
Restaurants
road networks
Roads
Roads & highways
sampling
Sampling methods
Transportation networks
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Summary:With the rapid development of location-based services, a particularly important aspect of start-up marketing research is to explore and characterize points of interest (PoIs) such as restaurants and hotels on maps. However, due to the lack of direct access to PoI databases, it is necessary to rely on existing APIs to query PoIs within a region and calculate PoI statistics. Unfortunately, public APIs generally impose a limit on the maximum number of queries. Therefore, we propose effective and efficient sampling methods based on road networks to sample PoIs on maps and provide unbiased estimators for calculating PoI statistics. In general, the more intense the roads, the denser the distribution of PoIs is within a region. Experimental results show that compared with state-of-the-art methods, our sampling methods improve the efficiency of aggregate statistical estimations.
ISSN:2095-2228
2095-2236
DOI:10.1007/s11704-016-6146-6