Topics include:
- Knowledge Graphs and Private Online Data Stores
- Privacy and Data Sovereignty
- Data Science, Data Mining and Machine Learning
- Open Source, R and GNU/Linux
- Spatial Reasoning
- Databases and Legacy Systems
- Frames Knowledge Representation and Expert Systems
2024 | 2023 | 2022 | 2021 | 2020 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 | 1998 | 1997 | 1996 | 1995 | 1994 | 1993 | 1992 | 1991 | 1990 | 1989 | 1988 | 1987 | 1986 | 1985
2024
Characterising Reproducibility Debt in Scientific Software: A Systematic Literature Review Zara Hassan, Christoph Treude, Michael Norrish, Graham Williams, ALex Potanin Journal of Systems & Software 2024.
Reproducibility Debt: Challenges and Future Pathways Zara Hassan, Christoph Treude, Michael Norrish, Graham Williams, ALex Potanin FSE Companion '24 Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering July 2024. Available locally.
2023
TRIC: A Triples Corrupter for Knowledge Graphs Asara Senaratne, Pouya Ghiasnezhad Omran, Peter Christen, and Graham Williams The Semantic Web: EWSC 2023 Satellite Events Hersonissos, Crete, Greece, May 28 - June 1 2023. Available locally
Unlocking health data for personal access and reuse Jess Moore, Sergio Rodriguez Mendez, Anushka Vidanage, Graham Williams, Jason King Vocabulary Symposium Canberra, April 2023. doi: 10.5281/zenodo.7834730.
Unsupervised Identification of Abnormal Nodes and Edges in Graphs. Asara Senaratne, Peter Christen, Graham Williams, Pouya G. Omran. Journal of Data and Information Quality, doi: 10.1145/3546912. July 2022. .
Rule-Based Knowledge Discovery via Anomaly Detection in Tabular Data. Asara Senaratne, Peter Christen, Graham Williams, and Pouya G. Omran. AAAI Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering California, USA, March 2023.
SEKA: Seeking Knowledge Graph Anomalies. Asara Senaratne, Pouya Ghiasnezhad Omran, Graham Williams, and Peter Christen. Companion proceedings of The Web Conference, Texas, USA, 2023
2022
Unsupervised Identification of Abnormal Nodes and Edges in Graphs. Asara Senaratne, Peter Christen, Graham Williams, and Pouya G. Omran. ACM Journal of Data and Information Quality volume 15 number 1, pp 1-37, 2022.
2021
Data Mining: 19th Australasian Conference on Data Mining, AusDM 2021. Yue Xu, Rosalind Wang, Anton Lord, Yee Ling Boo, Richi Nayak, Yanchang Zhao, Graham Williams. Communications in Computer and Information Science, doi: 10.1007/978-981-16-8531-6. Brisbane, QLD, Australia, December 14-15, 2021
Unsupervised Anomaly Detection in Knowledge Graphs. Asara
Senaratne, Pouya Ghiasnezhad Omran, Graham Williams, and Peter
Christen. The 10th International Joint Conference on Knowledge
Graphs, Thailand, 2021.
Development of the COVID-19 Real-Time Information System for Preparedness and Epidemic Response (CRISPER), Australia. Emma Field, Amalie Dyda, Michael Hewett, Haotian Weng, Jingjing Shi, Stephanie Curtis, Charlee Law, Lisa McHugh, Meru Sheel, Jess Moore, Luis Furuya-Kanamori, Priyanka Pillai, Paul Konings, Michael Purcell, Nigel Stocks, Graham Williams, Colleen Lau. Frontiers in Public Health, 9:753493.doi: 10.3389/fpubh.2021.753493, Nov 2021
Differential privacy for public health surveillance data: An innovative tool to optimise information sharing while protecting data confidentiality. Amalie Dyda, Michael Purcell, Stephanie Curtis, Emma Field, Priyanka Pillai, Kieran Ricardo, Haotian Weng, Graham Williams, Jessica Moore, Michael Hewett, Colleen Lau. Patterns 2(12), December 2021. Available locally.
2020
CRISPER: COVID-19 Real-Time Information System for Preparedness and Epidemic Response. Colleen Lau, Emma J Field, Michael Hewett, Priyanka Pillai, Kieran Ricardo, Luis Furuya-Kanamori, Stephanie Curtis, Nelson Lau, Meru Sheel, Lisa McHugh, Olivia Williams, Charlee J Law, Paul Konings, Ross Andrews, Nigel Stocks, Michael Purcell, Jess Moore, Graham Williams Australasian COVID-19 Virtual Conference, Public Health Association, Australia, 2020.
Starting With SOAP: rapid deployment of contract tracing in a
pandemic. Ellen Broad, Meru Sheel, Seth Lazar, Dilan Thampapillai,
Jochen Trumph, Amy McLennan, Kathy Reid, Caitlin Bentley, Katherine
Daniell, Ben Swift, Alwen Tiu, Graham
Williams, Atoosha Kasirzadeh, Tom Uren. ANU White Paper 2020. Github.
2018
Data Mining. Yee Ling Boo, David Stirling, Lianhua Chi, Lin Liu, Kok-Leong Ong, Graham Williams. 15th Australasian Conference, AusDM 2017, Melbourne, VIC, Australia, August 19-20, 2017. Revised Selected Papers. Springer, Communications in Computer and Information Science, Volume 845. Available from Springer, May 2018.
2017
The Essentials of Data Science: Knowledge discovery using R. Graham J. Williams. Chapman & Hall/CRC The R Series ISBN-10: 1138088633. Available from Amazon, August 2017, 342pp. Also see the Data Science Desktop Survival Guide.
WSRF: An R package for classification with scalable weighted subspace random forests. He Zhao, Graham J. Williams, Joshua Zhexue Huang. Journal of Statistical Software, Volume 77, Issue 1, 2017.
2016
Stratified Over-Sampling Bagging Method for Random Forests on Imbalanced Data. He Zhao, Xiaojun Chen, Tung Nguyen, Joshua Zhexue Huang, Graham J. Williams, Hui Chen. Pacific-Asia Workshop on Intelligence and Security Informatics PAISI 2016. Intelligence and Security Informatics. Springer Lecture Notes in Computer Science, Volume 9650, pp 63-72
2015
Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Longbing Cao, Chengqi Zhang, Thorsten Joachims, Geoff Webb, Dragos D. Margineantu, Graham Williams. KDD '15: The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Sydney NSW Australia. ISBN: 978-1-4503-3664-2, doi: 10.1145/2783258. August 2015
2014
Extensions to Quantile Regression Forests for Very High-Dimensional Data .
Nguyen Thanh Tung, Joshua Zhexue Huang, Imran Khan, Mark Junjie Li, Graham J. Williams. 18th
Pacific-Asia Conference on Knowledge Discovery and Data Mining PAKDD
2014. Lecture Notes in Computer Science, Volume 8444, May 2014, pp
247-258
Ensemble Clustering of High Dimensional Data with FastMap Projection.
Imran Khan, Joshua Zhexue Huang, Nguyen Thanh Tung, Graham J. Williams. Trends and
Applications in Knowledge Discovery and Data Mining, Lecture Notes in
Computer Science, Nov 2014, pp 483-493 . Available from the Publisher.
Big Data Opportunities and Challenges: Discussions from Data Analytics Perspectives.
Zhi-Hua Zhou, Nitesh V. Chawla, Yaochu Jin, and Graham J. Williams. IEEE
Computational Intelligence Magazine, Nov 2014. Outstanding Paper Award for 2014
(bestowed 2017). Available locally.
2013
Special Issue on Behavior Computing.
Longbing Cao, Philip S. Yu, Hiroshi Motoda, Graham J. Williams. Knowledge
and Information Systems, 37(2): 245-249, November
2013. . Available from the Publisher.
2012
Ensembles and model delivery for tax compliance..
Graham J. Williams.
Proceedings of the 18th ACM SIGKDD international conference on
Knowledge discovery and data mining, Beijing . Available from
the Publisher.
Classifying Very High-Dimensional Data with Random Forests built
from small subpaces. Baojun Xu, Joshua Z. Huang, Graham J. Williams, Q. Wany, Yunming
Ye. International Journal of Data Warehouse Mining. 8(2)
44-63.
Hybrid Weighted Random Forests for Classifying Very
High-Dimensional Data. Baojun Xu, Joshua Z. Huang, Graham J. Williams, Yunming Ye.
Submitted March 2012 . Available locally.
Hybrid Random Forests: Advantages of Mixed Trees in Classifying Text Data.
Baojun Xu, Joshua Z. Huang, Graham
J. Williams. PAKDD 2012 . Available locally.
Rattle and Other Data Mining Tales.
Graham Williams. in Journeys
to Data Mining Experiences of 15 Renowned
Scientists. Mohamed Medhat Gaber (Ed.). Springer, 2012, ISBN
978-3-642-28046-7 . Available locally and from the Publisher.
Classifying Very High-Dimensional Data with Random Forests Built from Small Subspaces.
Baojun Xu, Joshua Zhexue Huang, Graham
J. Williams, Qiang Wang, Yunming Ye. International Journal
of Data Warehousing and Mining, 8(2), March 2012. . Available locally.
Analysis of Cluster Migrations Using Self-Organizing Maps.
Denny, Peter Christen, Graham
Williams. Pacific Asia Conference on Knowledge Discovery and
Data Mining (PAKDD 2012),. Longbing Cao (Editor), Springer-Verlag,
Berlin Germany, p. 12.
Topic Oriented Community Detection through Social Objects and Link Analysis in Social Networks.
Zhongying Zhao, Shengzhong Feng, Qiang Wang, Joshua Z. Huang, Graham J. Williams, Jianping
Fan. Knowledge-Based Systems, 26:164-173, February
2012. . Available from the
Publisher .
2011
Data Mining with Rattle and R. The Art of Excavating Data for Knowledge Discovery..
Graham
Williams. Springer-Verlag. DOI:
10.1007/978-1-4419-9890-3. Available from Amazon. Earlier
and extended version available on Togaware.
2010
Visualizing Temporal Cluster Changes using Relative Density Self-Organizing Maps (ReDSOM).
Denny, Graham Williams, Peter
Christen. Knowledge and Information Systems, 25(2):281,
2010. . Available locally and from the
Publisher.
New Frontiers in Applied Data Mining.
Thanaruk Theeramunkong, Cholwich Nattee, Paulo J.L. Adeodato, Nitesh
Chawla, Peter Christen, Philippe Lenca, Josiah Poon and Graham Williams. Lecture Notes in
Computer Science. Volume 5669, September 2010,
Springer-Verlag. ISBN: 3-642-14640-4
2009
Rattle: A Data Mining GUI for R.
Graham Williams. The R
Journal, 1(2):45-55, December 2009. . Available locally and from the Journal.
PMML: An Open Standard for Sharing Models..
Wen-Ching Lin Alex Guazzelli, Michael Zeller and Graham Williams. The R Journal,
1(1):60-65, May 2009. . Available locally and from
the Journal.
2008
ReDSOM: Relative Density Visualization of Temporal Changes in Cluster Structures using Self-Organizing Maps.
Denny, Graham Williams, Peter
Christen. Proceedings of the 8th IEEE International Conference
on. Data Mining (ICDM08)
Pisa, Italy, December 2008. . Available locally.
Mining Unexpected Temporal Association: Applications in Detecting Adverse Drug Reactions.
Huidong Jin, Jie Chen, Hongxing He, Graham Williams, Chris Kelman,
Christine O’Keefe. IEEE Transactions on Information
Technology in Biomedicine . Vol 12, No. 4, July 2008. Available
locally.
Exploratory Hot Spot Profile Analysis using Interactive Visual Drill-Down Self-Organizing Maps.
Denny, Graham Williams, Peter
Christen. Proceedings of the 12th Pacific Asia Conference
on. Knowledge Discovery and Data Mining (PAKDD08). Osaka, Japan,
May 2008. Lecture Notes in Computer Science. . Available locally.
2007
DDDM2007: Domain Driven Data Mining..
Longbing Cao, Chengqi Zhang, Yanchang Zhao Philip S. Yu, Graham J. Williams. SIGKDD
Explorations 9(2): 84-86 (2007) . Available from the Publisher.
Exploratory multilevel hot spot analysis: Australian Taxation Office case study..
Denny, Graham Williams, Peter
Christen. Proceedings of the Australasian Data Mining
Conference, CRPIT Volume 70. AusDM07, Gold Coast, Australia,
December 2007. Available locally.
International Workshop on Domain Driven Data Mining. Philip Yu, Chengqi Zhang, Graham Williams, Longbing Cao. KDD07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, doi: 10.1145/1327942.1327946. August 2007
Open Source Data Mining Systems. Xiaojun Chen, Graham Williams, and Xiaofei Xu. Proceedings of the 11th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD07).. Nanjing, China, May 2007. Lecture Notes in Computer Science. Available locally.
2006
Mining Multiple Models.
Graham Williams.
Contributions To Probability And Statistics: Applications and
Challenges. Proceedings of the International Statistics
Workshop. University of Canberra 4 – 5 April 2005. Available
locally.
Neighborhood Density Method for Selecting Initial Cluster Centers in K-means Clustering.
Yunming Ye, Joshua Zhexue Huang, Xiaojun Chen, Shuigeng Zhou, Graham Williams. Proceedings of
the 10th Pacific Asia Conference on. Knowledge Discovery and Data
Mining (PAKDD06). Lecture Notes in Computer Science, Volume
3918, pp 189–198, 2006.
Frequency-based Rare Events Mining in Administrative Health Data.
Jie Chen, Huidong Jin, Hongxing He, Christine M. O’Keefe, Ross
Sparks, Graham Williams, Damien
McAullay, Chris Kelman. electronic Journal of Health
Informatics. 2006; Vol 1 (1): e4. Available locally
Identifying Risk Groups Associated with Colorectal Cancer.
Jie Chen, Hongxing He, Huidong Jin, Damien McAullay, Graham Williams, and Chris
Kelman. in Data Mining: Theory, Methodology, Techniques, and
Applications. Graham Williams
and Simeon Simoff (editors). Lecture Notes in Computer
Science. Volume 3755, Jan 2006, Springer-Verlag. ISBN:
3-540-32547-6
Data Mining: Theory, Methodology, Techniques, and Applications.
Graham Williams and Simeon Simoff
(editors). State-of-the-Art Survey, Lecture Notes in Artificial
Intelligence. Volume 3755, Jan 2006, Springer-Verlag. ISBN:
3-540-32547-6
2005
Proceedings of the 4th Australasian Data Mining Conference.
Simeon Simoff, Graham Williams,
John Galloway and Inna Kolyshkina (editors). University of
Technology, Sydney, December 2005, ISBN 1-86365-716-9.
Mining Risk Patterns in Medical Data.
Jiuyong Li, Ada Wai-chee Fu, Hongxing He, Jie Chen, Huidong Jin,
Damien McAullay, Graham Williams,
Ross Sparks, Chris Kelman. The Eleventh ACM SIGKDD
International Conference on Knowledge Discovery and Data Mining
(SIGKDD05), Industrial and Government Track . Chicago,
Illinois, USA 21-24 August 2005. Available locally.
Representing Association Classification Rules Mined from Health Data.
Jie Chen, Hongxing He, Jiuyong Li, Huidong Jin, Damien McAully, Graham Williams, Ross Sparks, Chris
Kelman. 9th International Conference on Knowledge-Based &
Intelligent Information & Engineering Systems (KES2005)
. Melbourne, Australia, 14-16 September
2005. Available locally as is a longer version.
Frequency-Based Temporal Pattern Mining in Health Data.
Jie Chen, Huidong Jin, Hongxing He, Christine O’Keefe, Ross
Sparks, Graham Williams, Damien
McAully, Chris Kelman. Australian Research Council Workshop on
Health Data Mining (HDM05) . Adelaide, South Australia,
11 April 2005. Available locally.
2004
Proceedings of the 3rd Australasian Data Mining Workshop.
Simeon J. Simoff, Graham Williams
(editors). Canberra, Australia, December 2004. Published
by University of Technology, Sydney, ISBN 0-9751724-1-7. Conference
web page: AusDM04
Exploratory Health Data Mining: Identifying Factors Associated with Colorectal Cancer.
Jie Chen, Hongxing He, Huidong Jin, Damien McAullay, Graham Williams, Chris Kelman.
3rd Australasian Data Mining Workshop . Cairns, Australia,
December 2004
CTAN Plans: The Comprehensive TeX Archive Network.
Robin Fairbairns, Jim Hefferon, Rainer Schoepf, Joachim Schrod, Graham
Williams, Reinhard Zierke. TUGboat Volume 24 (2004),
No. 2. Die TeXnische Komodie Volume 16 (3), November 2004
On-line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms.
Kenji Yamanishi, Jun-ichi Takeuchi, Graham Williams, Peter Milne.
International Journal of Data Mining and Knowledge Discovery.
Volume 8, Number 3, 2004, Pages 275-300, May 2004. Available locally.
Temporal Sequence Associations for Rare Events.
Jie Chen, Hongxing He, Graham
Williams, Huidong Jin. Proceedings of the 8th Pacific Asia
Conference on. Knowledge Discovery and Data Mining (PAKDD04)
. Available locally.
A new method of “pharmaco-vigilance” for automatically identifying Adverse Drug Reactions (ADRs) in large populations..
Simon Hawkins, Graham Williams,
Hongxing He, Lifang Gu, Jiuyong Li, Chris Kelman. Medinfo, 2004
. Available locally.
Exploring Possible Adverse Drug Reactions by Clustering Event Sequences.
Hongxing He, Graham Williams, Jie Chen, Simon Hawkins.
Submitted, 2004.
A Stock Flow Model for Health Care Workforce Prediction..
Houyuan Jiang, Hongxing He, Graham Williams, Lifang Gu, Rohan
Baxter. Fourth IMA International Conference on Quantitative
Modelling. in the Management of Healthcare. University of Salford,
UK, April 2004.
QLDS: Adverse drug reaction detection towards automation..
Graham Williams, Hongxing He, Jie
Chen, Huidong Jin, Damien McAullay, Ross Sparks, Jisheng Cui, Simon
Hawkins, and Chris Kelman. Technical Report CMIS 04/91, CSIRO
Mathematical and Information Sciences, Canberra, 2004.
Commonwealth Administrative Health Data Mining using Debian GNU/Linux..
Graham Williams. Linux and Open Source in Government, Australian
Linux Conference, January 2004. Available locally.
2003
Mining the Data Stream..
Graham Williams. Invited Plenary, International Conference on
Hybrid Intelligent Systems. Melbourne, Australia, December
2003. Available locally.
Proceedings of the 2nd Australasian Data Mining Workshop.
Simeon J. Simoff, Graham Williams,
Markus Hegland (editors). Canberra, Australia, December
2003. Published by University of Technology, Sydney, ISBN
0-9751724-1-7. Conference web page: AusDM03
Association Rule Discovery with Unbalanced Class Distributions.
Lifang Gu, Jiuyong Li, Hongxing He, Graham Williams, Simon Hawkins, Chris
Kelman. Proceedings of the 16th Australian Joint Conference
on. Artificial Intelligence (AI03)
Perth, Australia, December 2004. Lecture Notes in Artificial
Intelligence, Springer-Verlag. Available locally.
Temporal Event Mining of Linked Medical Claims Data.
Graham Williams, Chris Kelman,
Rohan Baxter, Lifang.Gu. Simon Hawkins, Hongxing He, Chris
Rainsford, Deanne Vickers. Proceedings of the PAKDD03 Workshop
on. Data Mining for Actionable Knowledge DMAK-2003. Seoul,
Korea, April 2003, pages 82-95. Available locally.
2002
Estimating Episodes of Care using Linked Medical Claims Data.
Graham Williams, Rohan Baxter,
Chris Kelman, Chris Rainsford, Hongxing He. Lifang.Gu, Deanne
Vickers, Simon Hawkins. Proceedings of the 15th Australian Joint
Conference on. Artificial Intelligence (AI02) Canberra,
Australia, December 2002. Lecture Notes in Artificial Intelligence,
Volume 2557, Springer-Verlag. Pages 660-671,
ISBN3-540-00197-2. Available locally.
Proceedings of the 1st Australian Data Mining Workshop.
Simeon J. Simoff, Graham Williams,
Markus Hegland (editors). Canberra, Australia, December
2002. Published by University of Technology, Sydney, ISBN
0-9750075-0-5. Conference web page: AusDM02
An Overview of Temporal Data Mining.
Weiqiang Lin, Mehmet A Orgun, Graham
Williams. Proceedings of the 1st Australian Data Mining
Workshop (AusDM02). Canberra,
Australia, December 2002. Editted by Simeon J. Simoff, Graham Williams, Markus
Hegland. Published by University of Technology, Sydney, Pages 83-90,
ISBN 0-9750075-0-5. Available locally.
A Comparative Study of Replicator Neural Networks for Outlier Detection in Data Mining.
Graham Williams, Rohan Baxter,
Hongxing He. Simon Hawkins, Lifang.Gu. Proceedings of the 2nd
IEEE International Conference on. Data Mining (ICDM02) Maebashi City,
Japan, December 2002. Pages 709–712, ISBN
0-7695-1754-4. Extended technical report CSIRO CMIS 02/102 available
locally. Available locally.
Outlier Detection Using Replicator Neural Networks.
Simon Hawkins, Hongxing He, Graham
Williams, Rohan Baxter. Proceedings of the 4th International
Conference on. Data Warehousing and Knowledge Discovery
(DaWaK02). Lecture Notes in Computer Science, Vol 2454,
Springer, 2002. Pages 170-180, ISBN 3-540-44123-9. Available locally.
Mining Temporal Patterns from Health Care Data.
Weiqiang Lin, Mehmut Orgun, Graham
Williams. Proceedings of the 4th International Conference
on. Data Warehousing and Knowledge Discovery (DaWaK02).
Lecture Notes in Computer Science, Vol 2454, Springer, 2002. Pages
221-231, ISBN 3-540-44123-9. Available locally.
2001
Artificial Intelligence in Industry.
Graham Williams and Dickson
Luckose. in Advances in Artificial Intelligence. Lecture
Notes in Computer Science, Volume 2112, Springer, 2001. pp 3-4,
ISBN 3540425977
Advances in Artificial Intelligence.
Ryszard Kowalczyk, Seng Wai Loke, Nancy Reed, Graham Williams. Workshop
Reader: Four Workshops held at PRICAI00. Melbourne, Australia,
August 2000, Revised Papers. Lecture
Notes in Computer Science, Volume 2112, Springer, 2001. ISBN
3540425977
Feature Selection for Pathology Laboratory Monitoring.
Simon Hawkins, Graham Williams,
Rohan Baxter. Topics in Health Information Management.
Volume 22 Number 1, August 2001, Pages 14-23
Advances in Knowledge Discovery and Data Mining.
David Cheung, Graham Williams, Qing
Li. Proceedings of the 5th Pacific Asia Conference
on. Knowledge Discovery and Data Mining (PAKDD01). Hong Kong,
China, April 2001. Lecture Notes in Artificial Intelligence, Volume
2035, Springer. ISBN 3540419101
Feature Selection for Temporal Health Records.
Rohan Baxter, Graham Williams,
Hongxing He. Advances in Knowledge Discovery and Data
Mining. Editted by David Cheung, Graham Williams, Qing Li. Lecture
Notes in Artificial Intelligence, Volume 2035, Springer, April
2001. Proceedings of the 5th Pacific Asia Conference on. Knowledge
Discovery and Data Mining (PAKDD01). Hong Kong, China, April
2001. Available from
springer.de and locally.
Temporal Data Mining Using Hidden Markov-Local Polynomial Models.
Weiqian Lin, Mehmet Orgun, Graham
Williams. Advances in Knowledge Discovery and Data
Mining. Editted by David Cheung, Graham Williams, Qing Li. Lecture
Notes in Artificial Intelligence, Volume 2035, Springer, April
2001. Proceedings of the 5th Pacific Asia Conference on. Knowledge
Discovery and Data Mining (PAKDD01). Hong Kong, China, April
2001. Available from
springer.de and locally.
Data Mining of Administrative Claims Data for Pathology Services.
Simon Hawkins, Graham Williams,
Rohan Baxter, Peter Christen, Michael Fett. Markus Hegland, Fuchun
Huang, Ole Nielsen, Tatiana Semanova, Andrew Smith. Hawaii
International Conference on System Sciences (HICSS-35). Workshop on
Data Mining in Health. January 2001, Hawaii, USA. Available
from
computer.org
2000
Temporal Data Mining using Multi-Level Local Polynomial Models.
Weiqiang Lin, Mehmet Orgun, Graham
Williams. Proceedings of the 2nd International Conference
on. Intelligent Data Engineering and Automated Learning
(IDEAL00). Lecture Notes in Computer Science, Volume 1983,
Springer. Hong Kong, December 2000
On-line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms.
Kenji Yamanishi, Jun-ichi Takeuchi, Graham Williams, Peter Milne.
Proceedings of the 6th ACM SIGKDD International Conference
on. Knowledge Discovery and Data Mining (KDD00). Boston, MA,
August 2000. Available locally and
from acm.org
Artificial Intelligence in Industry.
Dickson Lukose, Graham
Williams. Proceedings of the Symposium on the. Application
of Artificial Intelligence in Industry. Melbourne, Australia,
August 2000. ISBN 0730027937
Mining Taxation Data with Parallel BMARS.
Sergey Bakin, Markus Hegland, and Graham Williams. Parallel
Algorithms and Applications. Vol 15, pp 37-55, May
2000. Available locally.
Enterprise Data Mining: Case Studies and Integration in the
E-World. Zhexue Huang and Graham
Williams. The Fourth Pacific-Asia Conference on Knowledge
Discovery and Data Mining. Tutorial. April 18-20,
2000. Keihanna-Plaza, Kyoto, Japan. Available locally.
The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project.
Graham Williams, Irfan Altas,
Sergey Bakin, Peter Christen, Markus Hegland,. Alonso Marquez, Peter
Milne, Rajehndra Nagappan, and Stephen Roberts. In Large-Scale
Parallel Data Mining, State-of-the-Art Survey. Editted by
Mohammed J. Zaki and Ching-Tien Ho. Lecture Notes in Artificial
Intelligence, Volume 1759. Springer-Verlag, 2000
1999
An Overiew of ACSys Data Mining.
Graham Williams invited
presentation to the. Computational Techniques and Applications
Conference and Workshops (CTAC99). Canberra, September
1999. Available locally
Integrated Delivery of Data Mining.
Graham Williams.
International Workshop on Large-Scale Parallel. Knowledge Discovery
and Data Mining Systems (KDD99). San Diego, August 1999
Evolutionary Hot Spots Data Mining.
Graham Williams. Proceedings
of the 3rd Pacific-Asia Conference on. Knowledge Discovery and Data
Mining (PAKDD99). Beijing, April 1999. Available locally
Design of Decision Support Systems as Federated Information Systems.
D. J. Abel, Kerry Taylor, Gavin Walker, and Graham
Williams. Decision Support Systems for Sustainable
Development. Edited by Kersten, Mikolajuk, and Yeh. Kluwer
Academic Publishers, 1999
1998
Data Mining Tutorial.
Graham Williams.
SEAL98. Canberra, November 1998. Available locally
Evolvolutionary Techniques in Data Mining Interestingness.
Graham Williams. Workshop on
Evolutionary Computation. Canberra, October 1998
To What Extent can Data Mining be Proceduralised.
Graham Williams. Panel
Discussion. Pacific-Asia Conference on Knowledge Discovery and
Data Mining (PAKDD98). Melbourne, April 1998. Availabl locally
High Performance Data Managment Issues in Data Mining.
Graham Williams. Presented to
the Workshop on Parallel and Distributed Data Mining. Pacific-Asia
Conference on Knowledge Discovery and Data Mining (PAKDD98).
Melbourne, April 1998. Available locally
1997
Mining the Knowledge Mine: The Hot Spots Methodology for Mining Large Real World Databases.
Graham Williams, Zhexue
Huang. Advanced Topics in Artificial Intelligence.
Lecture Notes in Artificial Intelligence, Volume 1342, Springer,
1997. Pages 340–348. Available locally
PEPNet: Parallel Evolutionary Programming for Constructing Artificial Neural Networks.
Gerrit A. Riessen, Graham Williams,
Xin Yao. Sixth Annual Conference On Evolutionary Programming
(EP97). Indianapolis. Available locally
1996
A Case Study in Knowledge Acquisition for Insurance Risk Assessment using a KDD Methodology.
Graham Williams and Zhexue
Huang. Pacific Rim Knowledge Acquisition Workshop (PKAW96)
. October 1996, Sydney, Australia. Available locally
PEPNet: Parallel Evolutionary Artificial Neural Networks.
Gerrit Riessen, Xin Yao, Zhexue Huang, Peter Milne, and Graham Williams. Proceedings of
the 5th Australian Conference on. Neural Networks (ACNN96).
Available as a poster and abstract
KDD for Insurance Risk Assessment.
Graham Williams and Zhexue
Huang. CSIRO DIT Data Mining Technical Report
TR-DM-96014. March 1996. Available locally
Modelling the KDD Process.
Graham Williams and Zhexue
Huang. CSIRO DIT Data Mining Technical Report
TR-DM-96013. February 1996. Available locally
1995
Templates for Spatial Reasoning in Responsive GIS.
Graham Williams. International
Journal of Geographical Information Systems. 1995, Volume 9,
Number 2, Pages 117-131. Available locally
The Design of Decision Support Systems as Federated Information
Systems. D. J. Abel, K. L. Taylor, G. C. Walker, and Graham Williams. Proceedings of
the Decision Support Systems for Developing
Nations.. Taiwan. December 1995.
1994
The Virtual Database: A Tool for Migration from Legacy LIS.
D. J. Abel, B. C. Ooi, R. A. Power, K.-L. Tan, G. J. Williams, and
X. Zhou. In Proceedings of the 22nd Annual Conference of the
Australian Urban and Regional Information Systems Association AURISA
’94. Sydney, Australia, 1994
1993
The Virtual Database.
David J. Abel, Beng Chin Ooi, Robert A. Power, Kian-Lee Tan, Graham
Williams, and Xiafang Zhou. In Proceedings of the 21st Annual
Conference of the Australian Urban and Regional Information Systems
Association AURISA ’93. Sydney, Australia, 1993
Representing expectations in spatial information systems..
Graham Williams and Steve
G. Woods. Advances in Spatial Databases: Third International
Symposium, SSD ’93 . Edited by D. J. Abel and
B. C. Ooi. Lecture Notes in Computer Science, Volume 692,
Springer-Verlag, 1993
1990
Inducing and Combining Multiple Decision Trees.
Graham Williams. PhD Thesis,
Australian National University. Canberra, Australia,
1990. Available locally
1989
FrameUp: A frames formalism for expert systems.
Graham Williams. Australian
Computer Journal . Volume 21, Number 1, February 1989, Pages
33-40. Available locally
1988
Combining Decision Trees: Initial results from the MIL algorithm.
Graham Williams. Artificial
Intelligence Developments and Applications. Selected papers from
the first Australian. Joint Artificial Intelligence
Conference,. Sydney, Australia, 2-4 November, 1987. edited by
J. S. Gero and R. B. Stanton. North-Holland, Elsevier Science
Publishers. 1988, Pages 273-289. Available locally
The Design of Expert Systems for Environmental Management.
J. Richard Davis, Paul M. Nanninga and G. J. Williams. Readings in
Australian Geography. Proceedings of the 21st IAG
Conference. Perth, Australia, 1988
1987
Some Experiments in Decision Tree Induction.
G. J. Williams. Australian Computer Journal
. 1987, Volume 19, Number 2, Pages 84-91. Selected papers
from the Tenth Australian Computer Science Conference. Available locally.
1986
GEM: A Micro-Computer Based Expert System for Geographic Domains.
Graham Williams, J. Richard Davis
and Paul M. Nanninga. Proceedings of the Sixth International
Workshop and Conference on. Expert Systems and Their
Applications. Winner: Best student paper . Avignon,
France, 1986. Available locally together with the actual rule base.
Deficiencies of Expert Systems and Attempts at Improvement: A Survey.
Graham Williams. Proceedings
of the Ninth Australian Computer Science Conference
ACSC9. Australian National University, 1986
1985
Geographic Expert Systems for Resource Management.
J. Richard Davis, Paul M. Nanninga and
G. J. Williams. Proceedings of the First Australian Conference on
Applications of Expert Systems. Sydney, Australia, 1985
Final Report on the Development of an Expert System for Fire
Management in Kakadu National Park, NT. J. Richard Davis, Paul
M. Nanninga and G. J. Williams. CSIRO Division of
Water and Land resources. June 1985. Available locally.
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