| On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms K Yamanishi, JI Takeuchi, G Williams, P Milne Data Mining and Knowledge Discovery 8 (3), 275-300, 2004 | 753 | 2004 |
| Outlier detection using replicator neural networks S Hawkins, H He, G Williams, R Baxter International Conference on Data Warehousing and Knowledge Discovery, 170-180, 2002 | 694 | 2002 |
| Data mining with Rattle and R: The art of excavating data for knowledge discovery G Williams Springer Science & Business Media, 2011 | 494 | 2011 |
| Emergence of vancomycin-resistant enterococci in New York City TR Frieden, SS Munsiff, G Williams, Y Faur, B Kreiswirth, DE Low, ... The Lancet 342 (8863), 76-79, 1993 | 412 | 1993 |
| A comparative study of RNN for outlier detection in data mining G Williams, R Baxter, H He, S Hawkins, L Gu 2002 IEEE International Conference on Data Mining, 2002. Proceedings., 709-712, 2002 | 316 | 2002 |
| Big data opportunities and challenges: Discussions from data analytics perspectives [discussion forum] ZH Zhou, NV Chawla, Y Jin, GJ Williams IEEE Computational intelligence magazine 9 (4), 62-74, 2014 | 215 | 2014 |
| Rattle: a data mining GUI for R GJ Williams The R Journal 1 (2), 45-55, 2009 | 209 | 2009 |
| RI: an Expert in the Computer Systems Domain. JP McDermott AAAI 1, 269-271, 1980 | 206 | 1980 |
| PMML: An open standard for sharing models A Guazzelli, M Zeller, WC Lin, G Williams The R Journal 1 (1), 60-65, 2009 | 196 | 2009 |
| Topic oriented community detection through social objects and link analysis in social networks Z Zhao, S Feng, Q Wang, JZ Huang, GJ Williams, J Fan Knowledge-Based Systems 26, 164-173, 2012 | 172 | 2012 |
| KDD'15: Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining L Cao, C Zhang, T Joachims, GIB Webb, D Margineantu, G Williams Association for Computing Machinery (ACM), 2015 | 167 | 2015 |
| HEARSAY-II: A Domain-Independent Framework for Expert Systems. R Balzer, LD Erman, P London, C Williams AAAI 1, 108-110, 1980 | 118 | 1980 |
| Mining unexpected temporal associations: applications in detecting adverse drug reactions H Jin, J Chen, H He, GJ Williams, C Kelman, CM O'Keefe IEEE Transactions on Information Technology in Biomedicine 12 (4), 488-500, 2008 | 115 | 2008 |
| Mining risk patterns in medical data J Li, AW Fu, H He, J Chen, H Jin, D McAullay, G Williams, R Sparks, ... Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 108 | 2005 |
| Mining the knowledge mine GJ Williams, Z Huang Australian Joint Conference on Artificial Intelligence, 340-348, 1997 | 108 | 1997 |
| An Overview Of Temporal Data Mining. W Lin, MA Orgun, GJ Williams AusDM, 83-90, 2002 | 91 | 2002 |
| Cause of death and predictors of all‐cause mortality in anticoagulated patients with nonvalvular atrial fibrillation: data from ROCKET AF SD Pokorney, JP Piccini, SR Stevens, MR Patel, KS Pieper, JL Halperin, ... Journal of the American Heart Association 5 (3), e002197, 2016 | 85 | 2016 |
| Molecular subtyping of Clostridium perfringens by pulsed-field gel electrophoresis to facilitate food-borne-disease outbreak investigations SE Maslanka, JG Kerr, G Williams, JM Barbaree, LA Carson, JM Miller, ... Journal of clinical microbiology 37 (7), 2209-2214, 1999 | 83 | 1999 |
| Decision models for record linkage L Gu, R Baxter Data mining, 146-160, 2006 | 78* | 2006 |
| Data mining: Theory, methodology, techniques, and applications GJ Williams, SJ Simoff Springer, 2006 | 75 | 2006 |
