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Yun Sing Koh

Yun Sing KohYun Sing Koh is currently a lecturer in computer science at Auckland University of Technology (New Zealand). After completing a bachelor's degree in computer science and master’s degree in software engineering at the University of Malaya, she went onto do her PhD in computer science in Otago, New Zealand. Her current research interests include data mining, machine learning, and information retrieval. Read More Read Less

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1.
AI 2024: Advances in Artificial Intelligence
AI 2024: Advances in Artificial Intelligence
By: Mingming Gong, Yun Sing Koh, Wei Xiang, Derui Wang, Yiliao Song
Publisher: Springer Nature Switzerland AG
No Review Yet
AED375
Binding:
Paperback
Release:
24 Nov 2024
Language:
English
Available
Ships within 12-14 Days Explain..
2.
AI 2024: Advances in Artificial Intelligence
AI 2024: Advances in Artificial Intelligence
By: Mingming Gong, Yun Sing Koh, Wei Xiang, Derui Wang, Yiliao Song
Publisher: Springer Nature Switzerland AG
No Review Yet
AED334
Binding:
Paperback
Release:
24 Nov 2024
Language:
English
Available
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3.
Data Science and Machine Learning
Data Science and Machine Learning
By: Yun Sing Koh, Yee Ling Boo, Philippe Fournier-Viger, Sarah Erfani, Diana Benavides-Prado
Publisher: Springer Verlag, Singapore
No Review Yet
AED324
Binding:
Paperback
Release:
05 Dec 2023
Language:
English
International Edition
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4.
Data Mining
Data Mining
By: Yun Sing Koh, Simeon Simoff, Graham Williams, Yanchang Zhao, Yee Ling Boo
Publisher: Springer Verlag, Singapore
No Review Yet
AED353
Binding:
Paperback
Release:
06 Dec 2022
Language:
English
International Edition
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5.
New Frontiers in Applied Data Mining
New Frontiers in Applied Data Mining
By: Joshua Zhexue Huang, Jun Luo, James Bailey, Longbing Cao, Yun Sing Koh
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
No Review Yet
AED263
Binding:
Paperback
Release:
17 Feb 2012
Language:
English
International Edition
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6.
Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection
Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection
By: Nathan Rountree, Yun Sing Koh
Publisher: IGI Global
No Review Yet
AED876
Binding:
SA
Release:
31 Aug 2009
Language:
English
Out of Stock
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7.
Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection
Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection
By: Yun Sing Koh, Nathan Rountree
Publisher: IGI Global
No Review Yet
AED734
Binding:
Digital download and online
Release:
31 Aug 2009
Language:
English
Out of Stock
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8.
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
By: Yun Sing Koh, Gillian Dobbie, Saeed Ur Rehman, Shafiq Alam
Publisher: IGI Global
No Review Yet
AED37
Binding:
Digital download and online
Release:
31 May 2014
Language:
English
Out of Stock
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9.
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
By: Yun Sing Koh, Gillian Dobbie, Saeed Ur Rehman, Shafiq Alam
Publisher: IGI Global
No Review Yet
AED1,078
Binding:
Digital download and online
Release:
31 May 2014
Language:
English
Out of Stock
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10.
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
By: Yun Sing Koh, Gillian Dobbie, Saeed Ur Rehman, Shafiq Alam
Publisher: IGI Global
No Review Yet
AED1,301
Binding:
SA
Release:
31 May 2014
Language:
English
Out of Stock
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11.
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
By: Yun Sing Koh, Gillian Dobbie, Shafiq Alam, Saeed Ur Rehman (Unitec Institute of Technology, New Zealand)
Publisher: Information Science Reference
No Review Yet
AED1,078
Binding:
Digital (delivered electronically)
Release:
01 Jan 2014
Out of Stock
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