| Interestingness measures for data mining: A survey L Geng, HJ Hamilton ACM Computing Surveys (CSUR) 38 (3), 9-es, 2006 | 1669 | 2006 |
| A foundational approach to mining itemset utilities from databases H Yao, HJ Hamilton, CJ Butz Proceedings of the 2004 SIAM International Conference on Data Mining, 482-486, 2004 | 726 | 2004 |
| Mining itemset utilities from transaction databases H Yao, HJ Hamilton Data & Knowledge Engineering 59 (3), 603-626, 2006 | 487 | 2006 |
| Knowledge discovery and measures of interest RJ Hilderman, HJ Hamilton Springer Science & Business Media, 2013 | 282 | 2013 |
| Quality measures in data mining F Guillet, HJ Hamilton Springer Science & Business Media, 2007 | 256 | 2007 |
| Knowledge discovery and interestingness measures: A survey RJ Hilderman, HJ Hamilton Department of Computer Science, University of Regina, 1999 | 232 | 1999 |
| A unified framework for utility-based measures for mining itemsets H Yao, HJ Hamilton, L Geng Proc. of ACM SIGKDD 2nd Workshop on Utility-Based Data Mining, 28-37, 2006 | 207 | 2006 |
| DBRS: A density-based spatial clustering method with random sampling X Wang, HJ Hamilton Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference …, 2003 | 167 | 2003 |
| Mining functional dependencies from data H Yao, HJ Hamilton Data Mining and Knowledge Discovery 16, 197-219, 2008 | 159 | 2008 |
| Evaluation of interestingness measures for ranking discovered knowledge RJ Hilderman, HJ Hamilton Pacific-asia conference on knowledge discovery and data mining, 247-259, 2001 | 140 | 2001 |
| RIAC: a rule induction algorithm based on approximate classification HJ Hamilton, N Cercone, N Shan Computer Science Department, University of Regina, 1996 | 140 | 1996 |
| Efficient attribute-oriented generalization for knowledge discovery from large databases CL Carter, HJ Hamilton IEEE Transactions on knowledge and data engineering 10 (2), 193-208, 1998 | 133 | 1998 |
| FD/spl I. bar/Mine: discovering functional dependencies in a database using equivalences H Yao, HJ Hamilton, CJ Butz 2002 IEEE International Conference on Data Mining, 2002. Proceedings., 729-732, 2002 | 130 | 2002 |
| Extracting share frequent itemsets with infrequent subsets B Barber, HJ Hamilton Data Mining and Knowledge Discovery 7, 153-185, 2003 | 120 | 2003 |
| Using Rough Sets as Tools for Knowledge Discovery. N Shan, W Ziarko, HJ Hamilton, N Cercone KDD, 263-268, 1995 | 84 | 1995 |
| Choosing the right lens: Finding what is interesting in data mining L Geng, HJ Hamilton Quality measures in data mining, 3-24, 2007 | 80 | 2007 |
| Applying objective interestingness measures in data mining systems RJ Hilderman, HJ Hamilton European conference on principles of data mining and knowledge discovery …, 2000 | 79 | 2000 |
| Share based measures for itemsets CL Carter, HJ Hamilton, N Cercone Principles of Data Mining and Knowledge Discovery: First European Symposium …, 1997 | 76 | 1997 |
| Heuristic measures of interestingness RJ Hilderman, HJ Hamilton Principles of Data Mining and Knowledge Discovery: Third European Conference …, 1999 | 67 | 1999 |
| Density-based spatial clustering in the presence of obstacles and facilitators X Wang, C Rostoker, HJ Hamilton Knowledge Discovery in Databases: PKDD 2004: 8th European Conference on …, 2004 | 66 | 2004 |
