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

Ziting Zhou, Pengpeng Zhao, Victor S. Sheng, Jiajie Xu, Zhixu Li, Jian Wu, Zhiming Cui

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)582-592
Number of pages11
JournalFrontiers of Computer Science
Issue number3
StatePublished - Jun 1 2018


  • aggregate statistical estimation
  • road networks
  • sampling


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