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

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Abstract

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.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (NSFC) (Grant Nos. 61170020, 61402311, 61440053), and the US National Science Foundation (IIS-1115417).

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, 215006, China

    Ziting Zhou, Pengpeng Zhao, Jiajie Xu, Zhixu Li, Jian Wu & Zhiming Cui

  2. Department of Computer Science, University of Central Arkansas, Conway, AR, 72035, USA

    Victor S. Sheng

  3. Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, 210044, China

    Victor S. Sheng

Authors
  1. Ziting Zhou
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  2. Pengpeng Zhao
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  3. Victor S. Sheng
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  4. Jiajie Xu
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  5. Zhixu Li
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  6. Jian Wu
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  7. Zhiming Cui
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Corresponding author

Correspondence to Pengpeng Zhao.

Additional information

Ziting Zhou is a master candidate in the Department of Computer Science and Technology at Soochow University, China. She got a bachelor’s degree in computer science from Soochow University in 2014. Her main research interests are spatial data processing, recommendation system, and data mining.

Pengpeng Zhao is an associate professor in the Department of Computer Science and Technology at Soochow University, China. He received his PhD degree in computer science from Soochow University in 2008. His main research interests are in the area of data integration, spatial data processing, data Mining, machine learning, and crowd-sourcing.

Victor S. Sheng is an assistant professor of computer science at the University of Central Arkansas, USA and the founding director of Data Analytics Lab (DAL). He received his master’s degree in computer science from the University of New Brunswick, Canada in 2003, and his PhD degree in computer science from the Western University, Ontario, Canada in 2007. His research interests include data mining, machine learning, and related applications. He was an associate research scientist and NSERC postdoctoral follow in information systems at Stern Business School, New York University, USA after he obtained his PhD. Dr. Sheng is a member of the IEEE and a lifetime member of ACM. He received the best paper award runner-up from KDD’ 08, and the best paper award from ICDM’ 11. He is a PC member for a number of international conferences and a reviewer for several international journals.

Jiajie Xu is an associate professor at the School of Computer Science and Technology, Soochow University, China. He got his PhD and master’s degrees from the Swinburne University of Technology, Australia and the University of Queensland, Australia in 2011 and 2006 respectively. Before joining Soochow University in 2013, he worked as an assistant professor in the Institute of Software, Chinese Academy of Sciences, China. His research interests mainly include spatio-temporal database systems, big data analytics, and workflow systems.

Zhixu Li is an associate professor at the School of Computer Science and Technology in Soochow University, China. He got his PhD degree in computer science from the University of Queensland, Australia in 2013, and his master and bachelor degrees from Renmin University of China in 2009 and 2006 respectively. Before joining Soochow University, he has worked at King Abdullah University of Science and Technology, Saudi Arabia as a postdoc fellow from 2013 to 2014. His research interests mainly include data cleaning, data integration, web mining, knowledge discovery text, spatial data processing, data mining, machine learning, and crowd-sourcing.

Jian Wu is an assistant professor in the Institute of Intelligent Information Processing and Application at Soochow University, China. He received the MS and PhD degrees in computer science from Soochow University in 2004 and 2012 respectively. His research interests include computer vision, image processing, and pattern recognition. He has published several articles in computer vision, data mining, image processing and pattern recognition. He is a PC member for several international conferences and a reviewer for several international journals.

Zhiming Cui is a professor in the Institute of Intelligent Information Processing and Application at Soochow University, China. He is an outstanding expert of Jiangsu Province (China). He presided four National Natural Science Foundation of China. He has published several articles in computer vision, data mining, image processing, and pattern recognition. His research interests include deep Web, computer vision, image processing, and pattern recognition.

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Zhou, Z., Zhao, P., Sheng, V.S. et al. Efficient sampling methods for characterizing POIs on maps based on road networks. Front. Comput. Sci. 12, 582–592 (2018). https://doi.org/10.1007/s11704-016-6146-6

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  • DOI: https://doi.org/10.1007/s11704-016-6146-6

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