| Supervised clustering-algorithms and benefits CF Eick, N Zeidat, Z Zhao 16Th IEEE international conference on tools with artificial intelligence …, 2004 | 236 | 2004 |
| Finding regional co-location patterns for sets of continuous variables in spatial datasets CF Eick, R Parmar, W Ding, TF Stepinski, JP Nicot Proceedings of the 16th ACM SIGSPATIAL international conference on Advances …, 2008 | 99 | 2008 |
| Supporting polyploidy in genetic algorithms using dominance vectors BS Hadad, CF Eick Evolutionary Programming VI: 6th International Conference, EP97 Indianapolis …, 1997 | 88 | 1997 |
| A framework for regional association rule mining in spatial datasets W Ding, CF Eick, J Wang, X Yuan Sixth International Conference on Data Mining (ICDM'06), 851-856, 2006 | 66 | 2006 |
| MOSAIC: A proximity graph approach for agglomerative clustering J Choo, R Jiamthapthaksin, C Chen, OU Celepcikay, C Giusti, CF Eick Data Warehousing and Knowledge Discovery: 9th International Conference …, 2007 | 54 | 2007 |
| A framework for regional association rule mining and scoping in spatial datasets W Ding, CF Eick, X Yuan, J Wang, JP Nicot Geoinformatica 15, 1-28, 2011 | 51 | 2011 |
| Visualizing the evolution of genetic algorithm search processes WB Shine, CF Eick Proceedings of 1997 IEEE International Conference on Evolutionary …, 1997 | 50 | 1997 |
| Discovery of interesting regions in spatial data sets using supervised clustering CF Eick, B Vaezian, D Jiang, J Wang European Conference on Principles of Data Mining and Knowledge Discovery …, 2006 | 49 | 2006 |
| A Methodology for the Design and Transformation of Conceptual Schemas. CF Eick VLDB 91, 25-34, 1991 | 49 | 1991 |
| Acquisition of terminological knowledge using database design techniques CF Eick, PC Lockemann ACM SIGMOD Record 14 (4), 84-94, 1985 | 49 | 1985 |
| Using representative-based clustering for nearest neighbor dataset editing CF Eick, N Zeidat, R Vilalta Fourth IEEE International Conference on Data Mining (ICDM'04), 375-378, 2004 | 48 | 2004 |
| Class decomposition via clustering: a new framework for low-variance classifiers R Vilalta, MK Achari, CF Eick Third IEEE International Conference on Data Mining, 673-676, 2003 | 46 | 2003 |
| Towards region discovery in spatial datasets W Ding, R Jiamthapthaksin, R Parmar, D Jiang, TF Stepinski, CF Eick Advances in Knowledge Discovery and Data Mining: 12th Pacific-Asia …, 2008 | 39 | 2008 |
| Using clustering to learn distance functions for supervised similarity assessment CF Eick, A Rouhana, A Bagherjeiran, R Vilalta Engineering Applications of Artificial Intelligence 19 (4), 395-401, 2006 | 36 | 2006 |
| A database clustering methodology and tool TW Ryu, CF Eick Information Sciences 171 (1-3), 29-59, 2005 | 35 | 2005 |
| Integrating sets, rules, and data in an object-oriented environment B Czejdo, CF Eick, M Taylor IEEE Expert 8 (1), 59-66, 1993 | 35 | 1993 |
| Analyzing the composition of cities using spatial clustering Z Cao, S Wang, G Forestier, A Puissant, CF Eick Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing, 1-8, 2013 | 34 | 2013 |
| MASSON: discovering commonalities in collection of objects using genetic programming TW Ryu, CF Eick Proceedings of the 1st annual conference on genetic programming, 200-208, 1996 | 34 | 1996 |
| Adaptive clustering: Obtaining better clusters using feedback and past experience A Bagherjeiran, CF Eick, CS Chen, R Vilalta Fifth IEEE international conference on data mining (ICDM'05), 4 pp., 2005 | 31 | 2005 |
| Creating polygon models for spatial clusters F Akdag, CF Eick, G Chen Foundations of Intelligent Systems: 21st International Symposium, ISMIS 2014 …, 2014 | 30 | 2014 |
