Dr Yun Sing Koh

Research | Current

My current research interests include

  • Data Mining specifically Pattern Mining,
  • Data Stream Mining,
  • Machine Learning,
  • Information Retrieval.

 

Postgraduate supervision

Current PhD Supervision / Co-Supervision

Shuxiang Zhang (2018) Concept Drift Detection (co-supervised with Dr Pat Riddle)

Kylie Chen (2018) Towards a better understanding of diseases using semantic text mining (co-supervised with Dr Pat Riddle)

Alex (Yuxuan) Peng (2017) Deep Learning (co-supervised with Dr Pat Riddle)

Diana Benavides Prado (2016) - Meta Learning and Transfer Learning (co-supervised with Dr Pat Riddle)

Robert Anderson (2016) - Data Stream Mining (co-supervised with Prof Gill Dobbie)

Monica Bian (2015) - Social Network Mining (co-supervised with Prof Gill Dobbie)

Ian Wong (2016) - Feature Selection and Engineering (co-supervised with Prof Gill Dobbie)

Areas of expertise

Machine learning specifically in the area of unsupervised learning, data stream mining, and anomaly detection.

Selected publications and creative works (Research Outputs)

  • Fournier-Viger, P., Zhang, Y., Chun-Wei Lin, J., Fujita, H., & Koh, Y. S. (2019). Mining local and peak high utility itemsets. Information Sciences, 481, 344-367. 10.1016/j.ins.2018.12.070
  • Rajagopal, P., Ravana, S. D., Koh, Y. S., & Balakrishnan, V. (2019). Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment. ASLIB JOURNAL OF INFORMATION MANAGEMENT, 71 (1), 2-17. 10.1108/AJIM-04-2018-0086
  • Wong, I. S., Dobbie, G., & Koh, Y. S. (2019). Items2Data: Generating synthetic boolean datasets from itemsets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-12079-5_6
    Other University of Auckland co-authors: Gill Dobbie
  • Anderson, R., Koh, Y. S., & Dobbie, G. (2018). Predicting Concept Drift in Data Streams Using Metadata Clustering. Proceedings of the International Joint Conference on Neural Networks. 10.1109/IJCNN.2018.8489606
    Other University of Auckland co-authors: Gill Dobbie
  • Fournier-Viger, P., Zhang, Y., Lin, J. C. W., & Koh, Y. S. (2018). Discovering high utility change points in customer transaction data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-05090-0_33
  • Stirling, M., Koh, Y. S., Fournier-Viger, P., & Ravana, S. D. (2018). Concept drift detector selection for hoeffding adaptive trees. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-03991-2_65
  • Anderson, R., Koh, Y. S., & Dobbie, G. (2018). Lift-per-drift: An evaluation metric for classification frameworks with concept drift detection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-03991-2_57
    Other University of Auckland co-authors: Gill Dobbie
  • Bian, R., Koh, Y. S., Dobbie, G., & Divoli, A. (2018). OHC: Uncovering overlapping heterogeneous communities. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-03991-2_20
    Other University of Auckland co-authors: Gill Dobbie

Identifiers

Contact details

Primary office location

SCIENCE CENTRE 303S - Bldg 303S
Level 4, Room 485
38 PRINCES ST
AUCKLAND 1010
New Zealand

Web links