Skip to main content
SpringerLink
Log in

Discovering Organized POI Groups in a City

  • Conference paper
  • First Online:
Database Systems for Advanced Applications (DASFAA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9052))

Included in the following conference series:

  • 1239 Accesses

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Yuan, J., Zheng, Y., Xie, X.: Discovering regions of different functions in a city using human mobility and pois. In: SIGKDD, pp. 186–194. ACM (2012)

    Google Scholar 

  2. Fan, J., Li, G., Zhou, L., Chen, S., Hu, J.: Seal: spatio-textual similarity search. Proc. VLDB Endow. 5(9), 824–835 (2012)

    Article  Google Scholar 

  3. Bergroth, L., Hakonen, H., Raita, T.: A survey of longest common subsequence algorithms. In: String Processing and Information Retrieval, pp. 39–48. IEEE (2000)

    Google Scholar 

  4. Ester, M., Kriegel, H., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD, pp. 226–231 (1996)

    Google Scholar 

  5. Shi, J., Mamoulis, N., Wu, D., Cheung, D.W.: Density-based place clustering in geo-social networks. In: SIGMOD, pp. 99–110. ACM (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Yanxia Xu, Guanfeng Liu, Jiajie Xu & Lei Zhao

  2. School of ITEE, The University of Queensland, Brisbane, QLD, Australia

    Hongzhi Yin & Kai Zheng

Authors
  1. Yanxia Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guanfeng Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hongzhi Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jiajie Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kai Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lei Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lei Zhao .

Editor information

Editors and Affiliations

  1. Soochow University, Suzhou, China

    An Liu

  2. Nagoya University, Nagoya, Japan

    Yoshiharu Ishikawa

  3. Wuhan University, Wuhan, China

    Tieyun Qian

  4. University of Hong Kong, Hong Kong, China

    Sarana Nutanong

  5. Monash University, Clayton, Victoria, Australia

    Muhammad Aamir Cheema

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Xu, Y., Liu, G., Yin, H., Xu, J., Zheng, K., Zhao, L. (2015). Discovering Organized POI Groups in a City. In: Liu, A., Ishikawa, Y., Qian, T., Nutanong, S., Cheema, M. (eds) Database Systems for Advanced Applications. DASFAA 2015. Lecture Notes in Computer Science(), vol 9052. Springer, Cham. https://doi.org/10.1007/978-3-319-22324-7_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-22324-7_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22323-0

  • Online ISBN: 978-3-319-22324-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation