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IDMBS: An Interactive System to Find Interesting Co-location Patterns Using SVM

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Database Systems for Advanced Applications (DASFAA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13247))

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Abstract

Spatial co-location pattern mining is an important task in spatial data mining. However, traditional mining frameworks cannot help a particular user effectively discover interesting co-location patterns according to his specific interest because traditional mining algorithms decide the prevalence (frequency) of a co-location pattern only by a user-specified real number. Thus, in order to discover the user’s real interesting co-location patterns, in this demonstration, we present IDMBS (Interactive data mining based on support vector machine), an interactive mining system, to discover user-preferred co-location patterns based on SVM. With IDMBS, users only need to go through a few rounds of interactions to efficiently discover the user-preferred patterns. IDMBML contains a filtering algorithm and an SVM model. The patterns selected by the filtering algorithm are annotated by the user, and the SVM model trains these patterns in order to discover more user-preferred co-location patterns. IDMBS can effectively and accurately discover the user-preferred patterns.

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References

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Acknowledgements

This work was supported in part by grants (No. U1811264, No. U1711263, No. 61966009, No. 62006057, 61762027) from the National Natural Science Foundation of China, in part by grants (No. 2018GXNSFDA281045, No. 2019GXNSFBA245059) from the Natural Science Foundation of Guangxi Province, and in parts by grants (No. AD19245011) from the Key Research and Development Program of Guangxi Province.

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Authors and Affiliations

  1. Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin, 541004, China

    Liang Chang, Yuxiang Zhang & Xuguang Bao

  2. College of Cyber Security, Jinan University, Guangzhou, 510632, China

    Tianlong Gu

Authors
  1. Liang Chang
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  2. Yuxiang Zhang
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  3. Xuguang Bao
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  4. Tianlong Gu
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Corresponding author

Correspondence to Xuguang Bao .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Kanpur, India

    Arnab Bhattacharya

  2. National University of Singapore, Singapore, Singapore

    Janice Lee Mong Li

  3. University of California, Santa Barbara, Santa Barbara, CA, USA

    Divyakant Agrawal

  4. IIIT Hyderabad, Hyderabad, India

    P. Krishna Reddy

  5. Indraprastha Institute of Information Technology Delhi, New Delhi, India

    Mukesh Mohania

  6. Ashoka University, Sonepat, Haryana, India

    Anirban Mondal

  7. Indraprastha Institute of Information Technology Delhi, New Delhi, India

    Vikram Goyal

  8. University of Aizu, Aizu, Japan

    Rage Uday Kiran

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Chang, L., Zhang, Y., Bao, X., Gu, T. (2022). IDMBS: An Interactive System to Find Interesting Co-location Patterns Using SVM. In: Bhattacharya, A., et al. Database Systems for Advanced Applications. DASFAA 2022. Lecture Notes in Computer Science, vol 13247. Springer, Cham. https://doi.org/10.1007/978-3-031-00129-1_47

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  • DOI: https://doi.org/10.1007/978-3-031-00129-1_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-00128-4

  • Online ISBN: 978-3-031-00129-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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