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International Conference on Data Mining and Big Data

DMBD 2016: Data Mining and Big Data pp 115–122Cite as

A Geo-Social Data Model for Moving Objects

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

Abstract

In this paper, we combine moving-object database and social network systems and present a novel data model called Geo-Social-Moving (GSM) that enables the unified management of trajectories, underlying geographical space and social relationships for massive moving objects. A bulk of data types and corresponding operators are also proposed to facilitate geo-social queries on moving objects.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (Grant No. 41401460, 41271408) and the Key Research Program of the Chinese Academy of Sciences (Grant No. ZDRW-ZS-2016-6-3). And we also thank the anonymous referees for their helpful comments and suggestions.

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Authors and Affiliations

  1. State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Hengcai Zhang, Feng Lu & Jie Chen

  2. Fujian Collaborative Innovation Center for Big Data Applications in Governments, Fuzhou, 350003, China

    Hengcai Zhang, Feng Lu & Jie Chen

Authors
  1. Hengcai Zhang
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  2. Feng Lu
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  3. Jie Chen
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Corresponding author

Correspondence to Feng Lu .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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Cite this paper

Zhang, H., Lu, F., Chen, J. (2016). A Geo-Social Data Model for Moving Objects. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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