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2020 – today
- 2024
[j10]Yee Ling Boo, Manik Gupta, Weijia Zhang, Philippe Fournier-Viger:
Special Issue Editorial on "The Innovative Use of Data Science to Transform How We Work and Live". Data Sci. Eng. 9(1): 3-4 (2024)- [e4]Diana Benavides-Prado
, Sarah M. Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh:
Data Science and Machine Learning - 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023, Proceedings. Communications in Computer and Information Science 1943, Springer 2024, ISBN 978-981-99-8695-8 [contents] - 2023
- [c8]Abhinav Shrivastava, Humza Naseer, Booi Kam, Yee Ling Boo, Kok-Leong Ong:
Operationalising Analytics for Action: A Conceptual Framework Linking Embedded Analytics with Decision-Making Agility. ECIS 2023 - 2022
- [c7]Mohammad Alamgir Hossain, Alvedi Sabani, Sachithra Lokuge, Yee Ling Boo, Shahriar Kaisar:
Selection of Cloud Service Providers: A Fuzzy-set Qualitative Comparative Analysis Approach. TDIT (3) 2022: 422-433 - [e3]Laurence A. F. Park, Heitor Murilo Gomes, Maryam Gholami Doborjeh, Yee Ling Boo, Yun Sing Koh, Yanchang Zhao, Graham J. Williams, Simeon Simoff:
Data Mining - 20th Australasian Conference, AusDM 2022, Western Sydney, Australia, December 12-15, 2022, Proceedings. Communications in Computer and Information Science 1741, Springer 2022, ISBN 978-981-19-8745-8 [contents] - 2021
- [j9]Tahereh Pourhabibi, Kok-Leong Ong, Booi Hon Kam, Yee Ling Boo:
DarkNetExplorer (DNE): Exploring dark multi-layer networks beyond the resolution limit. Decis. Support Syst. 146: 113537 (2021) - [j8]Tahereh Pourhabibi, Kok-Leong Ong, Yee Ling Boo, Booi Kam:
Detecting covert communities in multi-layer networks: A network embedding approach. Future Gener. Comput. Syst. 124: 467-479 (2021) - [e2]Yue Xu, X. Rosalind Wang, Anton R. Lord, Yee Ling Boo, Richi Nayak, Yanchang Zhao, Graham J. Williams:
Data Mining - 19th Australasian Conference on Data Mining, AusDM, Brisbane, QLD, Australia, December 14-15, 2021, Proceedings. Communications in Computer and Information Science 1504, Springer 2021, ISBN 978-981-16-8530-9 [contents] - 2020
- [j7]Tahereh Pourhabibi, Kok-Leong Ong, Booi Kam, Yee Ling Boo:
Fraud detection: A systematic literature review of graph-based anomaly detection approaches. Decis. Support Syst. 133: 113303 (2020) - [j6]Alireza Moayedikia, William Yeoh, Kok-Leong Ong, Yee Ling Boo:
Framework and Literature Analysis for Crowdsourcing's Answer Aggregation. J. Comput. Inf. Syst. 60(1): 49-60 (2020)
2010 – 2019
- 2019
- [j5]Alireza Moayedikia, William Yeoh, Kok-Leong Ong, Yee Ling Boo:
Improving accuracy and lowering cost in crowdsourcing through an unsupervised expertise estimation approach. Decis. Support Syst. 122 (2019) - 2018
- [j4]Alireza Moayedikia, Kok-Leong Ong, Yee Ling Boo, William G. S. Yeoh:
Task assignment in microtask crowdsourcing platforms using learning automata. Eng. Appl. Artif. Intell. 74: 212-225 (2018) - [c6]Tahereh Pourhabibi, Yee Ling Boo, Kok-Leong Ong, Booi Kam, Xiuzhen Zhang:
Behavioral Analysis of Users for Spammer Detection in a Multiplex Social Network. AusDM 2018: 228-240 - [e1]Yee Ling Boo, David Stirling, Lianhua Chi, Lin Liu, Kok-Leong Ong, Graham Williams:
Data Mining - 15th Australasian Conference, AusDM 2017, Melbourne, VIC, Australia, August 19-20, 2017, Revised Selected Papers. Communications in Computer and Information Science 845, Springer 2018, ISBN 978-981-13-0291-6 [contents] - 2017
- [j3]Alireza Moayedikia, Kok-Leong Ong, Yee Ling Boo, William G. S. Yeoh, Richard Jensen:
Feature selection for high dimensional imbalanced class data using harmony search. Eng. Appl. Artif. Intell. 57: 38-49 (2017) - [c5]Alireza Moayedikia, Kok-Leong Ong, Yee Ling Boo, William Yeoh:
Meta-Heuristic Multi-objective Community Detection Based on Users' Attributes. AusDM 2017: 250-264 - 2016
- [c4]Alireza Moayedikia, Kok-Leong Ong, Yee Ling Boo, William Yeoh:
Bee Colony Based Worker Reliability Estimation Algorithm in Microtask Crowdsourcing. ICMLA 2016: 713-717 - 2015
- [j2]Neil Foshay, William Yeoh, Yee Ling Boo, Kok-Leong Ong, David Mattie:
A Comprehensive Diagnostic Framework for Evaluating Business Intelligence and Analytics Effectiveness. Australas. J. Inf. Syst. 19 (2015) - 2014
- [p1]Yee Ling Boo, Damminda Alahakoon:
Building Multi-modal Crime Profiles with Growing Self Organising Maps. Computational Intelligence in Digital Forensics 2014: 97-124 - 2013
- [j1]Ding-Wen Tan, William Yeoh, Yee Ling Boo, Soung-Yue Liew:
The Impact of Feature Selection: a Data-Mining Application in Direct Marketing. Intell. Syst. Account. Finance Manag. 20(1): 23-38 (2013) - 2011
- [c3]Yee Ling Boo, Damminda Alahakoon:
Identifying multi-view patterns with hierarchy and granularity based multimodal (HGM) cogntive model. GrC 2011: 71-76 - [c2]Yee Ling Boo, Damminda Alahakoon:
Clusters driven implementation of a brain inspired model for multi-view pattern identifications. ISDA 2011: 551-556
2000 – 2009
- 2009
- [b1]Yee Ling Boo:
Cluster driven approach for pattern identification and understanding. Monash University, Australia, 2009 - 2008
- [c1]Yee Ling Boo, Damminda Alahakoon:
Mining Multi-modal Crime Patterns at Different Levels of Granularity Using Hierarchical Clustering. CIMCA/IAWTIC/ISE 2008: 1268-1273
Coauthor Index
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