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Howard J. Hamilton: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Ning Shan, Wojciech Ziarko, Howard J. Hamilton, Nick Cercone
    Using Rough Sets as Tools for Knowledge Discovery. [Citation Graph (1, 0)][DBLP]
    KDD, 1995, pp:263-268 [Conf]
  2. Brock Barber, Howard J. Hamilton
    Attribute Selection Strategies fro Attribute-Oriented Generalization. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1996, pp:429-441 [Conf]
  3. Liqiang Geng, Howard J. Hamilton
    Finding Interesting Summaries in GenSpace Graphs Efficiently. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2004, pp:89-104 [Conf]
  4. Linhui Jiang, Howard J. Hamilton
    Methods for Mining Frequent Sequential Patterns. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2003, pp:486-491 [Conf]
  5. Kamran Karimi, Howard J. Hamilton
    RFCT: An Association-Based Causality Miner. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2002, pp:334-338 [Conf]
  6. Kamran Karimi, Howard J. Hamilton
    Discovering Temporal/Causal Rules: A Comparison of Methods. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2003, pp:175-189 [Conf]
  7. Jian Zhang, Howard J. Hamilton
    Learning English Syllabification Rules. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1998, pp:246-258 [Conf]
  8. Xin Wang, Howard J. Hamilton
    A Comparative Study of Two Density-Based Spatial Clustering Algorithms for Very Large Datasets. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2005, pp:120-132 [Conf]
  9. Xin Wang, Howard J. Hamilton
    Towards an Ontology-Based Spatial Clustering Framework. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2005, pp:205-216 [Conf]
  10. Yang Xiang, Xiaohua Hu, Nick Cercone, Howard J. Hamilton
    Learning Pseudo-independent Models: Analytical and Experimental Results. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2000, pp:227-239 [Conf]
  11. Howard J. Hamilton, Ning Shan, Wojciech Ziarko
    Machine Learning of Credible Classifications. [Citation Graph (0, 0)][DBLP]
    Australian Joint Conference on Artificial Intelligence, 1997, pp:330-339 [Conf]
  12. Ning Shan, Howard J. Hamilton, Nick Cercone
    Inducing and Using Decision Rules in the GRG Knowledge Discovery System. [Citation Graph (0, 0)][DBLP]
    ECML, 1997, pp:234-241 [Conf]
  13. Howard J. Hamilton
    Interestingness in Data Mining. [Citation Graph (0, 0)][DBLP]
    EGC, 2007, pp:3- [Conf]
  14. Leah Findlater, Howard J. Hamilton
    An Empirical Comparison of Methods for Iceberg-CUBE Construction. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2001, pp:244-248 [Conf]
  15. Avelino J. Gonzalez, Sylvia Daroszewski, Howard J. Hamilton
    Determining the Incremental Worth of Members of an Aggregate Set through Difference-Based Induction. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 1998, pp:245-249 [Conf]
  16. Howard J. Hamilton, Leah Findlater
    Looking Backward, Forward, and All Around: Temporal, Spatial, and Spatio-Temporal Data Mining. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2002, pp:481-485 [Conf]
  17. Howard J. Hamilton, Xuewei Wang, Y. Y. Yao
    WebAdaptor: Designing Adaptive Web Sites Using Data Mining Techniques. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2001, pp:128-132 [Conf]
  18. Robert J. Hilderman, Howard J. Hamilton, Brock Barber
    Ranking the Interestingness of Summaries from Data Mining Systems. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 1999, pp:100-106 [Conf]
  19. Dee Jay Randall, Howard J. Hamilton, Robert J. Hilderman
    A Technique for Generalizing Temporal Durations in Relational Databases. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 1998, pp:193-197 [Conf]
  20. Xin Wang, Howard J. Hamilton
    Clustering Spatial Data in the Presence of Obstacles. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2004, pp:- [Conf]
  21. Howard J. Hamilton, J. Michael Dyck
    Using the IIPS Framework to Specify Machine-Discovery Problems. [Citation Graph (0, 0)][DBLP]
    ICCI, 1992, pp:266-269 [Conf]
  22. Liqiang Geng, Howard J. Hamilton
    ESRS: A Case Selection Algorithm Using Extended Similarity-based Rough Sets. [Citation Graph (0, 0)][DBLP]
    ICDM, 2002, pp:609-612 [Conf]
  23. Hong Yao, Howard J. Hamilton, Cory J. Butz
    FD_Mine: Discovering Functional Dependencies in a Database Using Equivalences. [Citation Graph (0, 0)][DBLP]
    ICDM, 2002, pp:729-732 [Conf]
  24. Mahesh Shrestha, Howard J. Hamilton, Yiyu Yao, Ken Konkel, Liqiang Geng
    The PDD Framework for Detecting Categories of Peculiar Data. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:562-571 [Conf]
  25. Guichong Li, Howard J. Hamilton
    Searching for Pattern Rules. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:933-937 [Conf]
  26. Howard J. Hamilton, Robert J. Hilderman, Nick Cercone
    Attribute-oriented Induction Using Domain Generalization Graphs. [Citation Graph (0, 0)][DBLP]
    ICTAI, 1996, pp:246-253 [Conf]
  27. Robert J. Hilderman, Howard J. Hamilton
    Principles for mining summaries using objective measures of interestingness. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2000, pp:72-81 [Conf]
  28. Robert J. Hilderman, Liangchun Li, Howard J. Hamilton
    Data Visualization in the DB-Discover System. [Citation Graph (0, 0)][DBLP]
    ICTAI, 1997, pp:474-477 [Conf]
  29. Kamran Karimi, Howard J. Hamilton
    TimeSleuth: A Tool for Discovering Causal and Temporal Rules. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2002, pp:375-380 [Conf]
  30. Bradley P. Kram, James A. Hall, Howard J. Hamilton
    Support based measures applied to ice hockey scoring summaries. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2000, pp:352-0 [Conf]
  31. Kamran Karimi, Howard J. Hamilton
    Logical Decision Rules: Teaching C4.5 to Speak Prolog. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2000, pp:85-90 [Conf]
  32. Kamran Karimi, Howard J. Hamilton
    Discovering Temporal Rules from Temporally Ordered Data. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2002, pp:25-30 [Conf]
  33. Howard J. Hamilton, Dee Jay Randall
    Heuristic Selection of Aggregated Temporal Data for Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    IEA/AIE, 1999, pp:714-723 [Conf]
  34. Brock Barber, Howard J. Hamilton
    Parametric Algorithms for Mining Share-Frequent Itemsets. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2000, pp:562-572 [Conf]
  35. Brock Barber, Howard J. Hamilton
    A Comparison of Attribute Selection Strategies for Attribute-Oriented Generalization. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1997, pp:106-116 [Conf]
  36. Kamran Karimi, Howard J. Hamilton
    Finding Temporal Relations: Causal Bayesian Networks vs. C4.5. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2000, pp:266-273 [Conf]
  37. Ning Shan, Howard J. Hamilton, Nick Cercone
    Induction of Classification Rules from Imperfect Data. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1996, pp:118-127 [Conf]
  38. Jianna Jian Zhang, Howard J. Hamilton, Nick Cercone
    Learning English Grapheme Segmentation Using the Iterated Version Space Algorithm. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1999, pp:420-429 [Conf]
  39. Jian Zhang, Howard J. Hamilton
    Learning English Syllabification for Words. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1997, pp:177-186 [Conf]
  40. Ning Shan, Wojciech Ziarko, Howard J. Hamilton, Nick Cercone
    Discovering Classification Knowledge in Databases Using Rough Sets. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:271-274 [Conf]
  41. Howard J. Hamilton, Kamran Karimi
    The TIMERS II Algorithm for the Discovery of Causality. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2005, pp:744-750 [Conf]
  42. Robert J. Hilderman, Colin L. Carter, Howard J. Hamilton, Nick Cercone
    Mining Market Basket Data Using Share Measures and Characterized Itemsets. [Citation Graph (0, 0)][DBLP]
    PAKDD, 1998, pp:159-170 [Conf]
  43. Robert J. Hilderman, Howard J. Hamilton
    Evaluation of Interestingness Measures for Ranking Discovered Knowledge. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2001, pp:247-259 [Conf]
  44. Robert J. Hilderman, Howard J. Hamilton
    Heuristic for Ranking the Interestigness of Discovered Knowledge. [Citation Graph (0, 0)][DBLP]
    PAKDD, 1999, pp:204-209 [Conf]
  45. Kamran Karimi, Howard J. Hamilton
    Distinguishing Causal and Acausal Temporal Relations. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2003, pp:234-240 [Conf]
  46. Xin Wang, Howard J. Hamilton
    DBRS: A Density-Based Spatial Clustering Method with Random Sampling. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2003, pp:563-575 [Conf]
  47. Colin L. Carter, Howard J. Hamilton, Nick Cercone
    Share Based Measures for Itemsets. [Citation Graph (0, 0)][DBLP]
    PKDD, 1997, pp:14-24 [Conf]
  48. Brock Barber, Howard J. Hamilton
    Algorithms for Mining Share Frequent Itemsets Containing Infrequent Subsets. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:316-324 [Conf]
  49. Robert J. Hilderman, Howard J. Hamilton, Robert J. Kowalchuk, Nick Cercone
    Parallel Knowledge Discovery Using Domain Generalization Graphs. [Citation Graph (0, 0)][DBLP]
    PKDD, 1997, pp:25-35 [Conf]
  50. Howard J. Hamilton, Robert J. Hilderman, Liangchun Li, Dee Jay Randall
    Generalization Lattices. [Citation Graph (0, 0)][DBLP]
    PKDD, 1998, pp:328-336 [Conf]
  51. Robert J. Hilderman, Howard J. Hamilton
    Applying Objective Interestingness Measures in Data Mining Systems. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:432-439 [Conf]
  52. Robert J. Hilderman, Howard J. Hamilton
    Heuristic Measures of Interestingness. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:232-241 [Conf]
  53. Xin Wang, Camilo Rostoker, Howard J. Hamilton
    Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators. [Citation Graph (0, 0)][DBLP]
    PKDD, 2004, pp:446-458 [Conf]
  54. David R. Fudger, Howard J. Hamilton
    A Heuristic for Evaluating Databases for Knowledge Discovery with DBLEARN. [Citation Graph (0, 0)][DBLP]
    RSKD, 1993, pp:44-51 [Conf]
  55. Cory J. Butz, Hong Yao, Howard J. Hamilton
    Towards Jointree Propagation with Conditional Probability Distributions. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2004, pp:368-377 [Conf]
  56. 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. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2000, pp:642-646 [Conf]
  57. Y. Y. Yao, Howard J. Hamilton, Xuewei Wang
    PagePrompter: An Intelligent Web Agent Created Using Data Mining Techniques. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2002, pp:506-513 [Conf]
  58. Cory J. Butz, Hong Yao, Howard J. Hamilton
    A Non-local Coarsening Result in Granular Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 2003, pp:686-689 [Conf]
  59. Guichong Li, Howard J. Hamilton
    Basic Association Rules. [Citation Graph (0, 0)][DBLP]
    SDM, 2004, pp:- [Conf]
  60. Hong Yao, Howard J. Hamilton, Cory J. Butz
    A Foundational Approach to Mining Itemset Utilities from Databases. [Citation Graph (0, 0)][DBLP]
    SDM, 2004, pp:- [Conf]
  61. Xin Wang, Christine W. Chan, Howard J. Hamilton
    Design of knowledge-based systems with the ontology-domain-system approach. [Citation Graph (0, 0)][DBLP]
    SEKE, 2002, pp:233-236 [Conf]
  62. Robert J. Hilderman, Howard J. Hamilton
    Performance Analysis of a Regeneration-Based Dynamic Voting Algorithm. [Citation Graph (0, 0)][DBLP]
    Symposium on Reliable Distributed Systems, 1995, pp:196-205 [Conf]
  63. Scott D. Goodwin, Howard J. Hamilton, Eric Neufeld, Abdul Sattar, André Trudel
    Belief Revision in a Discrete Temporal Probability-Logic. [Citation Graph (0, 0)][DBLP]
    TIME, 1994, pp:113-120 [Conf]
  64. Howard J. Hamilton, Liqiang Geng, Leah Findlater, Dee Jay Randall
    Spatio-Temporal Data Mining with Expected Distribution Domain Generalization Graphs. [Citation Graph (0, 0)][DBLP]
    TIME, 2003, pp:181-191 [Conf]
  65. Dee Jay Randall, Howard J. Hamilton, Robert J. Hilderman
    Generalization for Calendar Attributes using Domain Generalization Graphs. [Citation Graph (0, 0)][DBLP]
    TIME, 1998, pp:177-184 [Conf]
  66. Howard J. Hamilton, Dee Jay Randall
    Data Mining with Calendar Attributes. [Citation Graph (0, 0)][DBLP]
    TSDM, 2000, pp:117-132 [Conf]
  67. Shannon Blyth, Howard J. Hamilton
    CrowdMixer: Multiple Agent Types in Situation-Based Crowd Simulations. [Citation Graph (0, 0)][DBLP]
    AIIDE, 2006, pp:15-20 [Conf]
  68. Scott D. Goodwin, Howard J. Hamilton
    It's About Time: An Introduction to the Special Issue on Temporal Representation and Reasoning. [Citation Graph (0, 0)][DBLP]
    Computational Intelligence, 1996, v:12, n:, pp:357-358 [Journal]
  69. Howard J. Hamilton, David R. Fudger
    Estimating DBLEARN's Potential for Knowledge Discovery in Databases. [Citation Graph (0, 0)][DBLP]
    Computational Intelligence, 1995, v:11, n:, pp:280-296 [Journal]
  70. Liqiang Geng, Howard J. Hamilton
    Interestingness measures for data mining: A survey. [Citation Graph (0, 0)][DBLP]
    ACM Comput. Surv., 2006, v:38, n:3, pp:- [Journal]
  71. Brock Barber, Howard J. Hamilton
    Extracting Share Frequent Itemsets with Infrequent Subsets. [Citation Graph (0, 0)][DBLP]
    Data Min. Knowl. Discov., 2003, v:7, n:2, pp:153-185 [Journal]
  72. Hong Yao, Howard J. Hamilton
    Mining itemset utilities from transaction databases. [Citation Graph (0, 0)][DBLP]
    Data Knowl. Eng., 2006, v:59, n:3, pp:603-626 [Journal]
  73. Leah Findlater, Howard J. Hamilton
    Iceberg-cube algorithms: An empirical evaluation on synthetic and real data. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2003, v:7, n:2, pp:77-97 [Journal]
  74. Robert J. Hilderman, Howard J. Hamilton
    Measuring the interestingness of discovered knowledge: A principled approach. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2003, v:7, n:4, pp:347-382 [Journal]
  75. Robert J. Hilderman, Howard J. Hamilton, Colin L. Carter, Nick Cercone
    Mining Association Rules from Market Basket Data using Share Measures and Characterized Itemsets. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 1998, v:7, n:2, pp:189-220 [Journal]
  76. Xin Wang, Howard J. Hamilton
    Clustering Spatial Data in The Presence of Obstacles. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2005, v:14, n:1-2, pp:177-198 [Journal]
  77. Dee Jay Randall, Howard J. Hamilton, Robert J. Hilderman
    Temporal Generalization with Domain Generalization Graphs. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 1999, v:13, n:2, pp:195-217 [Journal]
  78. Howard J. Hamilton, Liqiang Geng, Leah Findlater, Dee Jay Randall
    Efficient spatio-temporal data mining with GenSpace graphs. [Citation Graph (0, 0)][DBLP]
    J. Applied Logic, 2006, v:4, n:2, pp:192-214 [Journal]
  79. Howard J. Hamilton, Demyen Doug
    A machine-discovery approach to the evaluation of hashing techniques. [Citation Graph (0, 0)][DBLP]
    J. Exp. Theor. Artif. Intell., 2005, v:17, n:1-2, pp:45-62 [Journal]
  80. Brock Barber, Howard J. Hamilton
    Parametric Algorithms for Mining Share Frequent Itemsets. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2001, v:16, n:3, pp:277-293 [Journal]
  81. Robert J. Hilderman, Howard J. Hamilton, Nick Cercone
    Data Mining in Large Databases Using Domain Generalization Graphs. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 1999, v:13, n:3, pp:195-234 [Journal]
  82. Colin L. Carter, Howard J. Hamilton
    Efficient Attribute-Oriented Generalization for Knowledge Discovery from Large Databases. [Citation Graph (0, 9)][DBLP]
    IEEE Trans. Knowl. Data Eng., 1998, v:10, n:2, pp:193-208 [Journal]
  83. Robert J. Hilderman, Howard J. Hamilton
    A Note on Regeneration with Virtual Copies. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Software Eng., 1997, v:23, n:1, pp:56-59 [Journal]
  84. Liqiang Geng, Howard J. Hamilton, Larry Korba
    Expectation Propagation in GenSpace Graphs for Summarization. [Citation Graph (0, 0)][DBLP]
    DaWaK, 2007, pp:449-458 [Conf]

  85. Using Dependence Diagrams to Summarize Decision Rule Sets. [Citation Graph (, )][DBLP]


  86. Visualizing Privacy Implications of Access Control Policies in Social Network Systems. [Citation Graph (, )][DBLP]


  87. Generation and Interpretation of Temporal Decision Rules [Citation Graph (, )][DBLP]


  88. Mining functional dependencies from data. [Citation Graph (, )][DBLP]


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