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)

  • 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
  • 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
  • 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
  • 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
  • (2018). Mining local high utility itemsets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-319-98812-2_41
  • Chen, J. (2018). Vehicle emission prediction using remote sensing data and machine learning techniques The University of Auckland. ResearchSpace@Auckland.
    URL: http://hdl.handle.net/2292/37484
    Other University of Auckland co-authors: Jason Chen, Gill Dobbie
  • Samimi, P., Ravana, S. D., Webber, W., & Koh, Y. S. (2017). Effects of objective and subjective competence on the reliability of crowdsourced relevance judgments. INFORMATION RESEARCH-AN INTERNATIONAL ELECTRONIC JOURNAL, 22 (1)
  • Benavides-Prado, D., Koh, Y., & Riddle, P. (2017). AccGenSVM: Selectively transferring from previous hypotheses. In C. Sierra (Ed.) Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 1440-1446. Melbourne, Australia.
    Other University of Auckland co-authors: Diana Benavides Prado, Patricia Riddle

Identifiers

Contact details

Primary office location

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

Web links