| |
 |      |
                                         |
Note: Links lead to the DBLP on the Web. Howard J. Hamilton 57 Kamran Karimi , Howard J. Hamilton: Distinguishing Causal and Acausal Temporal Relations. PAKDD 2003 : 234-240 56 Xin Wang , Howard J. Hamilton: DBRS: A Density-Based Spatial Clustering Method with Random Sampling. PAKDD 2003 : 563-575 55 Cory J. Butz , Hong Yao , Howard J. Hamilton: A Non-local Coarsening Result in Granular Probabilistic Networks. RSFDGrC 2003 : 686-689 54 Brock Barber , Howard J. Hamilton: Extracting Share Frequent Itemsets with Infrequent Subsets. Data Mining and Knowledge Discovery 7 (2): 153-185 (2003) 53 Kamran Karimi , Howard J. Hamilton: RFCT: An Association-Based Causality Miner. Canadian Conference on AI 2002 : 334-338 52 Howard J. Hamilton, Leah Findlater : Looking Backward, Forward, and All Around: Temporal, Spatial, and Spatio-Temporal Data Mining. FLAIRS Conference 2002 : 481-485 51 Liqiang Geng , Howard J. Hamilton: ESRS: A Case Selection Algorithm Using Extended Similarity-based Rough Sets. ICDM 2002 : 609-612 50 Hong Yao , Howard J. Hamilton, Cory J. Butz : FD_Mine: Discovering Functional Dependencies in a Database Using Equivalences. ICDM 2002 : 729-732 49 Kamran Karimi , Howard J. Hamilton: Discovering Temporal Rules from Temporally Ordered Data. IDEAL 2002 : 25-30 48 Y. Y. Yao , Howard J. Hamilton, Xuewei Wang : PagePrompter: An Intelligent Web Agent Created Using Data Mining Techniques. Rough Sets and Current Trends in Computing 2002 : 506-513 47 Xin Wang , Christine W. Chan , Howard J. Hamilton: Design of knowledge-based systems with the ontology-domain-system approach. SEKE 2002 : 233-236 46 Howard J. Hamilton, Xuewei Wang , Y. Y. Yao : WebAdaptor: Designing Adaptive Web Sites Using Data Mining Techniques. FLAIRS Conference 2001 : 128-132 45 Leah Findlater , Howard J. Hamilton: An Empirical Comparison of Methods for Iceberg-CUBE Construction. FLAIRS Conference 2001 : 244-248 44 Robert J. Hilderman , Howard J. Hamilton: Evaluation of Interestingness Measures for Ranking Discovered Knowledge. PAKDD 2001 : 247-259 43 Brock Barber , Howard J. Hamilton: Parametric Algorithms for Mining Share Frequent Itemsets. JIIS 16 (3): 277-293 (2001) 42 Howard J. Hamilton: Advances in Artificial Intelligence, 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000, Montréal, Quebec, Canada, May 14-17, 2000, Proceedings. Springer 2000 41 Yang Xiang , Xiaohua Hu , Nick Cercone , Howard J. Hamilton: Learning Pseudo-independent Models: Analytical and Experimental Results. Canadian Conference on AI 2000 : 227-239 40 Kamran Karimi , Howard J. Hamilton: Logical Decision Rules: Teaching C4.5 to Speak Prolog. IDEAL 2000 : 85-90 39 Kamran Karimi , Howard J. Hamilton: Finding Temporal Relations: Causal Bayesian Networks vs. C4.5. ISMIS 2000 : 266-273 38 Brock Barber , Howard J. Hamilton: Parametric Algorithms for Mining Share-Frequent Itemsets. ISMIS 2000 : 562-572 37 Brock Barber , Howard J. Hamilton: Algorithms for Mining Share Frequent Itemsets Containing Infrequent Subsets. PKDD 2000 : 316-324 36 Robert J. Hilderman , Howard J. Hamilton: Applying Objective Interestingness Measures in Data Mining Systems. PKDD 2000 : 432-439 35 Kamran Karimi , Julia A. Johnson , Howard J. Hamilton: A Proposal for Including Behavior in the Process of Object Similarity Assessment with Examples from Artificial Life. Rough Sets and Current Trends in Computing 2000 : 642-646 34 Howard J. Hamilton, Dee Jay Randall : Data Mining with Calendar Attributes. TSDM 2000 : 117-132 33 Robert J. Hilderman , Howard J. Hamilton, Brock Barber : Ranking the Interestingness of Summaries from Data Mining Systems. FLAIRS Conference 1999 : 100-106 32 Howard J. Hamilton, Dee Jay Randall : Heuristic Selection of Aggregated Temporal Data for Knowledge Discovery. IEA/AIE 1999 : 714-723 31 Jianna Jian Zhang , Howard J. Hamilton, Nick Cercone : Learning English Grapheme Segmentation Using the Iterated Version Space Algorithm. ISMIS 1999 : 420-429 30 Robert J. Hilderman , Howard J. Hamilton: Heuristic for Ranking the Interestigness of Discovered Knowledge. PAKDD 1999 : 204-209 29 Robert J. Hilderman , Howard J. Hamilton: Heuristic Measures of Interestingness. PKDD 1999 : 232-241 28 Dee Jay Randall , Howard J. Hamilton, Robert J. Hilderman : Temporal Generalization with Domain Generalization Graphs. IJPRAI 13 (2): 195-217 (1999) 27 Robert J. Hilderman , Howard J. Hamilton, Nick Cercone : Data Mining in Large Databases Using Domain Generalization Graphs. JIIS 13 (3): 195-234 (1999) 26 Jian Zhang , Howard J. Hamilton: Learning English Syllabification Rules. Canadian Conference on AI 1998 : 246-258 25 Dee Jay Randall , Howard J. Hamilton, Robert J. Hilderman : A Technique for Generalizing Temporal Durations in Relational Databases. FLAIRS Conference 1998 : 193-197 24 Avelino J. Gonzalez , Sylvia Daroszewski , Howard J. Hamilton: Determining the Incremental Worth of Members of an Aggregate Set through Difference-Based Induction. FLAIRS Conference 1998 : 245-249 23 Robert J. Hilderman , Colin L. Carter , Howard J. Hamilton, Nick Cercone : Mining Market Basket Data Using Share Measures and Characterized Itemsets. PAKDD 1998 : 159-170 22 Howard J. Hamilton, Robert J. Hilderman , Liangchun Li , Dee Jay Randall : Generalization Lattices. PKDD 1998 : 328-336 21 Dee Jay Randall , Howard J. Hamilton, Robert J. Hilderman : Generalization for Calendar Attributes using Domain Generalization Graphs. TIME 1998 : 177-184 20 Colin L. Carter , Howard J. Hamilton: Efficient Attribute-Oriented Generalization for Knowledge Discovery from Large Databases. TKDE 10 (2): 193-208 (1998) 19 Howard J. Hamilton, Ning Shan , Wojciech Ziarko : Machine Learning of Credible Classifications. Australian Joint Conference on Artificial Intelligence 1997 : 330-339 18 Ning Shan , Howard J. Hamilton, Nick Cercone : Inducing and Using Decision Rules in the GRG Knowledge Discovery System. ECML 1997 : 234-241 17 Robert J. Hilderman , Liangchun Li , Howard J. Hamilton: Data Visualization in the DB-Discover System. ICTAI 1997 : 474-477 16 Brock Barber , Howard J. Hamilton: A Comparison of Attribute Selection Strategies for Attribute-Oriented Generalization. ISMIS 1997 : 106-116 15 Jian Zhang , Howard J. Hamilton: Learning English Syllabification for Words. ISMIS 1997 : 177-186 14 Colin L. Carter , Howard J. Hamilton, Nick Cercone : Share Based Measures for Itemsets. PKDD 1997 : 14-24 13 Robert J. Hilderman , Howard J. Hamilton, Robert J. Kowalchuk , Nick Cercone : Parallel Knowledge Discovery Using Domain Generalization Graphs. PKDD 1997 : 25-35 12 Robert J. Hilderman , Howard J. Hamilton: A Note on Regeneration with Virtual Copies. TSE 23 (1): 56-59 (1997) 11 Brock Barber , Howard J. Hamilton: Attribute Selection Strategies fro Attribute-Oriented Generalization. Canadian Conference on AI 1996 : 429-441 10 Howard J. Hamilton, Robert J. Hilderman , Nick Cercone : Attribute-oriented Induction Using Domain Generalization Graphs. ICTAI 1996 : 246-253 9 Ning Shan , Howard J. Hamilton, Nick Cercone : Induction of Classification Rules from Imperfect Data. ISMIS 1996 : 118-127 8 Ning Shan , Wojciech Ziarko , Howard J. Hamilton, Nick Cercone : Discovering Classification Knowledge in Databases Using Rough Sets. KDD 1996 : 271-274 7 Scott D. Goodwin , Howard J. Hamilton: It's About Time: An Introduction to the Special Issue on Temporal Representation and Reasoning. Computational Intelligence 12 : 357-358 (1996) 6 Ning Shan , Wojciech Ziarko , Howard J. Hamilton, Nick Cercone : Using Rough Sets as Tools for Knowledge Discovery. KDD 1995 : 263-268 5 Robert J. Hilderman , Howard J. Hamilton: Performance Analysis of a Regeneration-Based Dynamic Voting Algorithm. Symposium on Reliable Distributed Systems 1995 : 196-205 4 Howard J. Hamilton, David R. Fudger : Estimating DBLEARN's Potential for Knowledge Discovery in Databases. Computational Intelligence 11 : 280-296 (1995) 3 Scott D. Goodwin , Howard J. Hamilton, Eric Neufeld , Abdul Sattar , André Trudel : Belief Revision in a Discrete Temporal Probability-Logic. TIME 1994 : 113-120 2 David R. Fudger , Howard J. Hamilton: A Heuristic for Evaluating Databases for Knowledge Discovery with DBLEARN. RSKD 1993 : 44-51 1 Howard J. Hamilton, J. Michael Dyck : Using the IIPS Framework to Specify Machine-Discovery Problems. ICCI 1992 : 266-269  DiSC'03 © 2003 Association for Computing Machinery |
