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Current Trends in Learning from Data Streams

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Big Data Analytics (BDA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13147))

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Abstract

This article presents our recent work on the topic of learning from data streams. We focus on emerging topics, including fraud detection, learning from rare cases, and hyper-parameter tuning for streaming data.

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References

  1. Ali, M., Azad, M., Centeno, M., Hao, F., Van Moorsel, A.: Consumer-facing technology fraud: economics, attack methods and potential solutions. Future Gener. Comput. Syst. 100, 408–427 (2019)

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  8. Veloso, B., Tabassum, S., Martins, C., Espanha, R., Azevedo, R., Gama, J.: Interconnect bypass fraud detection: a case study. Ann. Telecommun., 75(9), 583–596 (2020). https://doi.org/10.1007/s12243-020-00808-w

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Acknowledgements

This work was supported by the CHIST-ERA grant CHIST-ERA-19-XAI-012, and project CHIST-ERA/0004/2019 funded by FCT.

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Authors and Affiliations

  1. LIAAD - INESC TEC, Porto, Portugal

    João Gama, Bruno Veloso, Ehsan Aminian & Rita P. Ribeiro

  2. University Portucalense, Porto, Portugal

    Bruno Veloso

  3. University of Porto, Porto, Portugal

    João Gama, Bruno Veloso, Ehsan Aminian & Rita P. Ribeiro

Authors
  1. João Gama
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  2. Bruno Veloso
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  3. Ehsan Aminian
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  4. Rita P. Ribeiro
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Corresponding author

Correspondence to João Gama .

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Editors and Affiliations

  1. University of Hyderabad, Hyderabad, India

    Satish Narayana Srirama

  2. Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

  3. University of Cincinnati, Cincinnati, OH, USA

    Raj Bhatnagar

  4. Indian Institute of Information Technology Allahabad, Prayagraj, India

    Sonali Agarwal

  5. International Institute of Information Technology, Hyderabad, India

    P. Krishna Reddy

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Gama, J., Veloso, B., Aminian, E., Ribeiro, R.P. (2021). Current Trends in Learning from Data Streams. In: Srirama, S.N., Lin, J.CW., Bhatnagar, R., Agarwal, S., Reddy, P.K. (eds) Big Data Analytics. BDA 2021. Lecture Notes in Computer Science(), vol 13147. Springer, Cham. https://doi.org/10.1007/978-3-030-93620-4_14

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  • DOI: https://doi.org/10.1007/978-3-030-93620-4_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93619-8

  • Online ISBN: 978-3-030-93620-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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