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Discovering Interesting Co-location Patterns Interactively Using Ontologies

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Database Systems for Advanced Applications (DASFAA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10179))

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Abstract

Co-location pattern mining, which discovers feature types that frequently appear in a nearby geographic region, plays an important role in spatial data mining. Common frameworks for mining co-location patterns generate numerous redundant patterns. Thus, several methods were proposed to overcome this drawback. However, most of these methods did not guarantee that the extracted co-location patterns were interesting for being generally based on statistical information. Thus, it is crucial to help the decision-maker choose interesting co-location patterns with an efficient interactive procedure. This paper proposed an interactive approach to discover interesting co-location patterns. First, ontologies were used to improve the integration of user knowledge. Second, an interactive process was designed to collaborate with the user to find interesting co-location patterns efficiently. Finally, a filter was designed to reduce the number of discovered co-location patterns in the result set further. The experimental results on both synthetic and real data sets demonstrated the effectiveness of our approach.

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Acknowledgements

This work was supported in part by grants (No. 61472346, No.61262069, No. 61662086) from the National Natural Science Foundation of China, by grants (No. 2016FA026, No. 2015FB149, and No. 2015FB114) from the Science Foundation of Yunnan Province and by the Spectrum Sensing and borderlands Security Key Laboratory of Universities in Yunnan (C6165903).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming, 650091, China

    Xuguang Bao & Lizhen Wang

Authors
  1. Xuguang Bao
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  2. Lizhen Wang
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Correspondence to Lizhen Wang .

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Editors and Affiliations

  1. Royal Melbourne Institute of Technology , Melbourne, Australia

    Zhifeng Bao

  2. Northwestern University , Evanston, Illinois, USA

    Goce Trajcevski

  3. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

  4. The University of Queensland , Brisbane, Queensland, Australia

    Wen Hua

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Bao, X., Wang, L. (2017). Discovering Interesting Co-location Patterns Interactively Using Ontologies. In: Bao, Z., Trajcevski, G., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10179. Springer, Cham. https://doi.org/10.1007/978-3-319-55705-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-55705-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55704-5

  • Online ISBN: 978-3-319-55705-2

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