Geoffrey I. Webb (also known as Geoff Webb) is Professor of Computer Science at Monash University, Founder and Director of Data Mining software development and consultancy company G. I. Webb and Associates, and former Editor-in-Chief of the journal Data Mining and Knowledge Discovery. Before joining Monash University he was on the faculty at Griffith University from 1986 to 1988 and then at Deakin University from 1988 to 2002.
Webb has published more than 200 scientific papers in the fields of machine learning, data science, data mining, data analytics, big data and user modeling. He is an editor of the Encyclopedia of Machine Learning.
Webb created the Averaged One-Dependence Estimators machine learning algorithm and its generalization Averaged N-Dependence Estimators and has worked extensively on statistically sound association rule learning. His early work included advocating the use of machine learning to create black box user models; interactive machine learning; and one of the first approaches to association rule learning using minimum support and confidence.
Webb's awards include inaugural Eureka Prize for Excellence in Data Science, 2017, IEEE Fellow, Australian Computer Society ICT Researcher of the Year Award 2016, the IEEE International Conference on Data Mining Outstanding Service Award, an Australian Research Council Outstanding Researcher Award and multiple Australian Research Council Discovery Grants.
Webb is a Foundation Member of the Editorial Advisory Board of the journal Statistical Analysis and Data Mining, Wiley Inter Science. He has served on the Editorial Boards of the journals Machine Learning, ACM Transactions on Knowledge Discovery in Data,User Modeling and User Adapted Interaction, and Knowledge and Information Systems.
Webb was elected to the ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) Executive Committee in 2017.
- "G. I. Webb and Associates"
- "Data Mining and Knowledge Discovery Journal" Retrieved on 2013-10-20.
- Geoff Webb publications indexed by Google Scholar
- "Encyclopedia of Machine Learning"
- Webb, Geoffrey; J. Boughton; Z. Wang (2005). "Not So Naive Bayes: Aggregating One-Dependence Estimators". Machine Learning. 58 (1): 5–24. CiteSeerX 10.1.1.3.7847. doi:10.1007/s10994-005-4258-6.
- Webb, Geoffrey; J. Boughton; F. Zheng; K.M. Ting; H. Salem (2012). "Learning by extrapolation from marginal to full-multivariate probability distributions: Decreasingly naive Bayesian classification". Machine Learning. 86 (2): 233–272. doi:10.1007/s10994-011-5263-6.
- Webb, Geoffrey (2007). "Discovering Significant Patterns". Machine Learning. 68 (1): 1–33. doi:10.1007/s10994-007-5006-x.
- Webb, Geoffrey (2008). "Layered Critical Values: A Powerful Direct-Adjustment Approach to Discovering Significant Patterns". Machine Learning. 71 (2–3): 307–323. doi:10.1007/s10994-008-5046-x.
- Webb, Geoffrey (2010). "Self-Sufficient Itemsets: An Approach to Screening Potentially Interesting Associations Between Items". Transactions on Knowledge Discovery from Data. 4: 3:1–3:20. doi:10.1145/1644873.1644876.
- Webb, Geoffrey (2011). "Filtered-top-k Association Discovery". WIREs Data Mining and Knowledge Discovery. 1 (3): 183–192. CiteSeerX 10.1.1.228.2541. doi:10.1002/widm.28.
- Webb, Geoffrey; M. Kuzmycz (1996). "Feature based modelling: a methodology for producing coherent, consistent, dynamically changing models of agents' competencies". User Modeling and User-Adapted Interaction. 5 (2): 117–150. doi:10.1007/BF01099758.
- Webb, Geoffrey (1996). "Integrating Machine Learning With Knowledge Acquisition Through Direct Interaction With Domain Experts". Knowledge-Based Systems. 9 (4): 253–266. CiteSeerX 10.1.1.228.3037. doi:10.1016/0950-7051(96)01033-7.
- Webb, Geoffrey; J. Wells; Z. Zheng (1999). "An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition". Machine Learning. 35 (1): 5–14. doi:10.1023/A:1007504102006.
- Webb, Geoffrey (1989). "A Machine Learning Approach to Student Modelling" (PDF). Proceedings of the Third Australian Joint Conference on Artificial Intelligence (AI 89). pp. 195–205.
- "Eureka Prize Winners 2017"
- "IEEE Fellows 2015"
- ACS Digital Disruptors Awards Winners 2016
- ""IEEE Data Mining Awards"". Archived from the original on 2017-08-18. Retrieved 2013-10-20.
- Discovery Projects Funding Outcomes for Projects Commencing in 2014
- ""Discovery Projects Funding Outcomes"". Archived from the original on 2013-10-23. Retrieved 2013-10-20.
- Statistical Analysis and Data Mining Editorial Board
- About SIGKDD