Graham J. Williams

Publication Activity (10 Years)

Years Active: 1987-2023
Publications (10 Years): 5

Top Topics

Anomaly Detection

Knowledge Discovery

Top Venues

PAKDD Workshops

ESWC (Satellite Events)

Publications

Asara Senaratne, Peter Christen, Graham J. Williams, Pouya Ghiasnezhad Omran
Rule-Based Knowledge Discovery via Anomaly Detection in Tabular Data. AAAI Spring Symposium: MAKE (2023)
Asara Senaratne, Pouya Ghiasnezhad Omran, Peter Christen, Graham J. Williams
TRIC: A Triples Corrupter for Knowledge Graphs. ESWC (Satellite Events) (2023)
Subudhi Asara Senaratne, Peter Christen, Graham J. Williams, Pouya Ghiasnezhad Omran
Unsupervised Identification of Abnormal Nodes and Edges in Graphs. ACM J. Data Inf. Qual. 15 (1) (2023)
Asara Senaratne, Pouya Ghiasnezhad Omran, Graham J. Williams, Peter Christen
Unsupervised Anomaly Detection in Knowledge Graphs. IJCKG (2021)
He Zhao, Xiaojun Chen, Thanh-Tung Nguyen, Joshua Zhexue Huang, Graham J. Williams, Hui Chen
Stratified Over-Sampling Bagging Method for Random Forests on Imbalanced Data. PAISI (2016)
Imran Khan, Joshua Zhexue Huang, Nguyen Thanh Tung, Graham J. Williams
Ensemble Clustering of High Dimensional Data with FastMap Projection. PAKDD Workshops (2014)
Nguyen Thanh Tung, Joshua Zhexue Huang, Imran Khan, Mark Junjie Li, Graham J. Williams
Extensions to Quantile Regression Forests for Very High-Dimensional Data. PAKDD (2) (2014)
Zhongying Zhao, Shengzhong Feng, Qiang Wang, Joshua Zhexue Huang, Graham J. Williams, Jianping Fan
Topic oriented community detection through social objects and link analysis in social networks. Knowl. Based Syst. 26 (2012)
Baoxun Xu, Joshua Zhexue Huang, Graham J. Williams, Qiang Wang, Yunming Ye
Classifying Very High-Dimensional Data with Random Forests Built from Small Subspaces. Int. J. Data Warehous. Min. 8 (2) (2012)
Baoxun Xu, Joshua Zhexue Huang, Graham J. Williams, Mark Junjie Li, Yunming Ye
Hybrid Random Forests: Advantages of Mixed Trees in Classifying Text Data. PAKDD (1) (2012)
Denny, Peter Christen, Graham J. Williams
Analysis of Cluster Migrations Using Self-Organizing Maps. PAKDD Workshops (2011)
Denny, Graham J. Williams, Peter Christen
Visualizing temporal cluster changes using Relative Density Self-Organizing Maps. Knowl. Inf. Syst. 25 (2) (2010)
Graham J. Williams
Rattle: A Data Mining GUI for R. R J. 1 (2) (2009)
Denny, Graham J. Williams, Peter Christen
Exploratory Hot Spot Profile Analysis Using Interactive Visual Drill-Down Self-Organizing Maps. PAKDD (2008)
Denny, Graham J. Williams, Peter Christen
ReDSOM: Relative Density Visualization of Temporal Changes in Cluster Structures Using Self-Organizing Maps. ICDM (2008)
Huidong Jin, Jie Chen, Hongxing He, Graham J. Williams, Chris Kelman, Christine M. O'Keefe
Mining Unexpected Temporal Associations: Applications in Detecting Adverse Drug Reactions. IEEE Trans. Inf. Technol. Biomed. 12 (4) (2008)
Xiaojun Chen, Yunming Ye, Graham J. Williams, Xiaofei Xu
A Survey of Open Source Data Mining Systems. PAKDD Workshops (2007)
Denny, Graham J. Williams, Peter Christen
Exploratory Multilevel Hot Spot Analysis: Australian Taxation Office Case Study. AusDM (2007)
Yunming Ye, Joshua Zhexue Huang, Xiaojun Chen, Shuigeng Zhou, Graham J. Williams, Xiaofei Xu
Neighborhood Density Method for Selecting Initial Cluster Centers in K-Means Clustering. PAKDD (2006)
Damien McAullay, Graham J. Williams, Jie Chen, Huidong Jin
A Delivery Framework for Health Data Mining and Analytics. ACSC (2005)
Jie Chen, Hongxing He, Jiuyong Li, Huidong Jin, Damien McAullay, Graham J. Williams, Ross Sparks, Chris Kelman
Representing Association Classification Rules Mined from Health Data. KES (3) (2005)
Jiuyong Li, Ada Wai-Chee Fu, Hongxing He, Jie Chen, Huidong Jin, Damien McAullay, Graham J. Williams, Ross Sparks, Chris Kelman
Mining risk patterns in medical data. KDD (2005)
Hongxing He, Graham J. Williams, Jie Chen, Simon Hawkins, Chris Kelman
Exploring Possible Adverse Drug Reactions by Clustering Event Sequences. DaWaK (2004)
Tatiana Semenova, Markus Hegland, Warwick Graco, Graham J. Williams
Conceptual Mining of Large Administrative Health Data. PAKDD (2004)
Kenji Yamanishi, Jun'ichi Takeuchi, Graham J. Williams, Peter Milne
On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms. Data Min. Knowl. Discov. 8 (3) (2004)
Jie Chen, Hongxing He, Graham J. Williams, Huidong Jin
Temporal Sequence Associations for Rare Events. PAKDD (2004)
Graham J. Williams
Mining the Data Stream. HIS (2003)
Lifang Gu, Jiuyong Li, Hongxing He, Graham J. Williams, Simon Hawkins, Chris Kelman
Association Rule Discovery with Unbalanced Class Distributions. Australian Conference on Artificial Intelligence (2003)
Graham J. Williams, Rohan A. Baxter, Chris Kelman, Chris P. Rainsford, Hongxing He, Lifang Gu, Deanne Vickers, Simon Hawkins
Estimating Episodes of Care Using Linked Medical Claims Data. Australian Joint Conference on Artificial Intelligence (2002)
Weiqiang Lin, Mehmet A. Orgun, Graham J. Williams
Mining Temporal Patterns from Health Care Data. DaWaK (2002)
Simon Hawkins, Hongxing He, Graham J. Williams, Rohan A. Baxter
Outlier Detection Using Replicator Neural Networks. DaWaK (2002)
Graham J. Williams, Rohan A. Baxter, Hongxing He, Simon Hawkins, Lifang Gu
A Comparative Study of RNN for Outlier Detection in Data Mining. ICDM (2002)
Weiqiang Lin, Mehmet A. Orgun, Graham J. Williams
An Overview Of Temporal Data Mining. AusDM (2002)
Weiqiang Lin, Mehmet A. Orgun, Graham J. Williams
Temporal Data Mining Using Hidden Markov-Local Polynomial Models. PAKDD (2001)
Simon Hawkins, Graham J. Williams, Rohan A. Baxter, Peter Christen, Michael J. Fett, Markus Hegland, Fuchun Huang, Ole Møller Nielsen, Tatiana Semenova, Andrew Smith
Data Mining of Administrative Claims Data for Pathology Services. HICSS (2001)
Rohan A. Baxter, Graham J. Williams, Hongxing He
Feature Selection for Temporal Health Records. PAKDD (2001)
Graham J. Williams, Dickson Lukose
Artificial Intelligence in Industry. PRICAI Workshops (2000)
Sergey Bakin, Markus Hegland, Graham J. Williams
Mining taxation data with parallel BMARS. Parallel Algorithms Appl. 15 (1-2) (2000)
Weiqiang Lin, Mehmet A. Orgun, Graham J. Williams
Temporal Data Mining Using Multilevel-Local Polynominal Models. IDEAL (2000)
Kenji Yamanishi, Jun'ichi Takeuchi, Graham J. Williams, Peter Milne
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms. KDD (2000)
Graham J. Williams
Evolutionary Hot Spots Data Mining - An Architecture for Exploring for Interesting Discoveries. PAKDD (1999)
Graham J. Williams, Irfan Altas, Sergey Bakin, Peter Christen, Markus Hegland, Alonso Marquez, Peter Milne, Rajehndra Nagappan, Stephen G. Roberts
The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project. Large-Scale Parallel Data Mining (1999)
Gerrit Riessen, Graham J. Williams, Xin Yao
PEPNet: Parallel Evolutionary Programming for Constructing Artificial Neural Networks. Evolutionary Programming (1997)
Graham J. Williams, Zhexue Huang
Mining the Knowledge Mine: The Hot Spots Methodology for Mining Large Real World Databases. Australian Joint Conference on Artificial Intelligence (1997)
Graham J. Williams
Templates for Spatial Reasoning in Responsive Geographical Information Systems. Int. J. Geogr. Inf. Sci. 9 (2) (1995)
Graham J. Williams, Steven G. Woods
Representing Expectations in Spatial Information Systems - A Case Study. SSD (1993)
Graham J. Williams
FrameUP: A Frames Formalism for Expert Systems. Aust. Comput. J. 21 (1) (1989)
Graham J. Williams
Some Experiments in Decision Tree Induction. Aust. Comput. J. 19 (2) (1987)