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Vertical Data Mining from Relational Data and Its Application to COVID-19 Data

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Big Data Analyses, Services, and Smart Data (BIGDAS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 899))

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Abstract

Nowadays, big data are everywhere. These big data can be of different degrees of veracity (e.g., precise, imprecise and uncertain data). Many of them are open data and are stored in relational databases. Embedded in these big data are valuable information and knowledge, which can be discovered by data mining. Frequent pattern mining is a popular data mining task within the realm of data science. In this paper, we present data science techniques for vertical data mining—in particular, vertical mining of frequently occurring patterns—from these relational data. For illustration, we discuss applications of the vertical data mining for the discovery of knowledge and useful information from real-life epidemiological data about coronavirus disease 2019 (COVID-19) and economic data.

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Notes

  1. 1.

    https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page.

  2. 2.

    https://opendata.cityofnewyork.us/.

  3. 3.

    https://winnipegtransit.com/en/open-data/on-time-performance/.

  4. 4.

    https://data.winnipeg.ca/.

  5. 5.

    https://open.canada.ca/.

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Acknowledgements

This project is partially supported by (i) Birla Institute of Technology & Science (BITS) - Pilani, (ii) China Scholarship Council (CSC), (iii) Mitacs (Canada), (iv) Nanjing University, (v) Natural Sciences and Engineering Research Council of Canada (NSERC), (vi) Tongji University, as well as (vii) University of Manitoba.

Author information

Authors and Affiliations

  1. Birla Institute of Technology and Science (BITS) - Pilani, Jhunjhunu, RJ, India

    Pranjal Gupta

  2. University of Manitoba, Winnipeg, MB, Canada

    Pranjal Gupta, Calvin S. H. Hoi, Carson K. Leung, Ye Yuan, Xiaoke Zhang & Zhida Zhang

  3. University of Waterloo, Waterloo, ON, Canada

    Pranjal Gupta

  4. Nanjing University, Nanjing, JS, China

    Xiaoke Zhang

  5. The University of British Columbia (UBC), Vancouver, BC, Canada

    Xiaoke Zhang

  6. Tongji University, Shanghai, China

    Zhida Zhang

  7. Columbia University, New York, NY, USA

    Zhida Zhang

Authors
  1. Pranjal Gupta
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  2. Calvin S. H. Hoi
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  3. Carson K. Leung
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  4. Ye Yuan
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  5. Xiaoke Zhang
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  6. Zhida Zhang
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Corresponding author

Correspondence to Carson K. Leung .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Inha University, Incheon, Korea (Republic of)

    Wookey Lee

  2. Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada

    Carson K. Leung

  3. Department of Computer Science, Chungbuk National University, Cheongju, Korea (Republic of)

    Aziz Nasridinov

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Gupta, P., Hoi, C.S.H., Leung, C.K., Yuan, Y., Zhang, X., Zhang, Z. (2021). Vertical Data Mining from Relational Data and Its Application to COVID-19 Data. In: Lee, W., Leung, C.K., Nasridinov, A. (eds) Big Data Analyses, Services, and Smart Data. BIGDAS 2018. Advances in Intelligent Systems and Computing, vol 899. Springer, Singapore. https://doi.org/10.1007/978-981-15-8731-3_8

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