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Robert J. Hilderman

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2010 – 2019

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2016
[j6]
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Obaid Ullah Malik, Robert J. Hilderman, Howard J. Hamilton, Richard Dosselmann:
Retail price time series imputation. Int. J. Bus. Intell. Data Min. 11(1): 49-62 (2016)
[c34]
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Credell Simeon, Howard J. Hamilton, Robert J. Hilderman:
Word Segmentation Algorithms with Lexical Resources for Hashtag Classification. DSAA 2016: 743-751
2015
[c33]
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Credell Simeon, Robert J. Hilderman:
Evaluating the Effectiveness of Hashtags as Predictors of the Sentiment of Tweets. Discovery Science 2015: 251-265
[c32]
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Credell Simeon, Robert J. Hilderman:
Using Combined Lexical Resources to Identify Hashtag Types. WASSA@EMNLP 2015: 169-174
2012
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Mondelle Simeon, Robert J. Hilderman, Howard J. Hamilton:
Mining Interesting Correlated Contrast Sets. SGAI Conf. 2012: 49-62
2011
[c30]
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Mondelle Simeon, Robert J. Hilderman:
COSINE: A Vertical Group Difference Approach to Contrast Set Mining. Canadian AI 2011: 359-371
[c29]
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Mondelle Simeon, Robert J. Hilderman:
GENCCS: A Correlated Group Difference Approach to Contrast Set Mining. MLDM 2011: 140-154
2010
[c28]
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Garrett Nicolai, Robert J. Hilderman:
Algorithms for Evolving No-Limit Texas Hold'em Poker Playing Agents. IJCCI (ICEC) 2010: 20-32
[c27]
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Garrett Nicolai, Robert J. Hilderman:
Countering Evolutionary Forgetting in No-Limit Texas Hold'em Poker Agents. IJCCI (Selected Papers) 2010: 31-48

2000 – 2009

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2009
[c26]
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Mondelle Simeon, Robert J. Hilderman:
An Empirical Study of Category Skew on Feature Selection for Text Categorization. Canadian AI 2009: 249-252
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Garrett Nicolai, Robert J. Hilderman:
No-Limit Texas Hold'em Poker agents created with evolutionary neural networks. CIG 2009: 125-131
2008
[c24]
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Mondelle Simeon, Robert J. Hilderman:
Categorical Proportional Difference: A Feature Selection Method for Text Categorization. AusDM 2008: 201-208
2007
[c23]
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Brien Beattie, Garrett Nicolai, David Gerhard, Robert J. Hilderman:
Pattern Classification in No-Limit Poker: A Head-Start Evolutionary Approach. Canadian AI 2007: 204-215
[c22]
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Timothy Maciag, Daryl H. Hepting, Robert J. Hilderman, Dominik Slezak:
Evaluation of a Dominance-Based Rough Set Approach to Interface Design. FBIT 2007: 409-416
[c21]
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Mondelle Simeon, Robert J. Hilderman:
Exploratory Quantitative Contrast Set Mining: A Discretization Approach. ICTAI (2) 2007: 124-131
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Timothy Maciag, Daryl H. Hepting, Dominik Slezak, Robert J. Hilderman:
Mining Associations for Interface Design. RSKT 2007: 109-117
[p1]
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Robert J. Hilderman, Terry Peckham:
Statistical Methodologies for Mining Potentially Interesting Contrast Sets. Quality Measures in Data Mining 2007: 153-177
2006
[c19]
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Trevor N. Mansuy, Robert J. Hilderman:
A Characterization of Wordnet Features in Boolean Models For Text Classification. AusDM 2006: 103-109
[c18]
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Trevor N. Mansuy, Robert J. Hilderman:
Evaluating WordNet Features in Text Classification Models. FLAIRS 2006: 568-573
2003
[j5]
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Robert J. Hilderman, Howard J. Hamilton:
Measuring the interestingness of discovered knowledge: A principled approach. Intell. Data Anal. 7(4): 347-382 (2003)
[c17]
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Trevor N. Mansuy, Robert J. Hilderman:
FormFormatter: A Software Tool for Generating Mouse-Optional User Interfaces in Visual Basic Applications. IASSE 2003: 172-177
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Robert J. Hilderman:
Predicting Itemset Sales Profiles with Share Measures and Repeat-Buying Theory. IDEAL 2003: 789-795
2002
[c15]
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Robert J. Hilderman:
The Lorenz Dominance Order as a Measure of Interestingness in KDD. PAKDD 2002: 177-185
2001
[c14]
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Robert J. Hilderman, Howard J. Hamilton:
Evaluation of Interestingness Measures for Ranking Discovered Knowledge. PAKDD 2001: 247-259
2000
[c13]
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Robert J. Hilderman, Howard J. Hamilton:
Principles for mining summaries using objective measures of interestingness. ICTAI 2000: 72-81
[c12]
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Robert J. Hilderman, Howard J. Hamilton:
Applying Objective Interestingness Measures in Data Mining Systems. PKDD 2000: 432-439

1990 – 1999

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1999
[j4]
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Dee Jay Randall, Howard J. Hamilton, Robert J. Hilderman:
Temporal Generalization with Domain Generalization Graphs. Int. J. Pattern Recognit. Artif. Intell. 13(2): 195-217 (1999)
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Robert J. Hilderman, Howard J. Hamilton, Nick Cercone:
Data Mining in Large Databases Using Domain Generalization Graphs. J. Intell. Inf. Syst. 13(3): 195-234 (1999)
[c11]
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Robert J. Hilderman, Howard J. Hamilton, Brock Barber:
Ranking the Interestingness of Summaries from Data Mining Systems. FLAIRS 1999: 100-106
[c10]
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Robert J. Hilderman, Howard J. Hamilton:
Heuristic for Ranking the Interestigness of Discovered Knowledge. PAKDD 1999: 204-209
[c9]
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Robert J. Hilderman, Howard J. Hamilton:
Heuristic Measures of Interestingness. PKDD 1999: 232-241
1998
[j2]
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Robert J. Hilderman, Howard J. Hamilton, Colin L. Carter, Nick Cercone:
Mining Association Rules from Market Basket Data using Share Measures and Characterized Itemsets. Int. J. Artif. Intell. Tools 7(2): 189-220 (1998)
[c8]
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Dee Jay Randall, Howard J. Hamilton, Robert J. Hilderman:
A Technique for Generalizing Temporal Durations in Relational Databases. FLAIRS 1998: 193-197
[c7]
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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
[c6]
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Howard J. Hamilton, Robert J. Hilderman, Liangchun Li, Dee Jay Randall:
Generalization Lattices. PKDD 1998: 328-336
[c5]
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Dee Jay Randall, Howard J. Hamilton, Robert J. Hilderman:
Generalization for Calendar Attributes using Domain Generalization Graphs. TIME 1998: 177-184
1997
[j1]
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Robert J. Hilderman, Howard J. Hamilton:
A Note on Regeneration with Virtual Copies. IEEE Trans. Software Eng. 23(1): 56-59 (1997)
[c4]
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Robert J. Hilderman, Liangchun Li, Howard J. Hamilton:
Data Visualization in the DB-Discover System. ICTAI 1997: 474-477
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Robert J. Hilderman, Howard J. Hamilton, Robert J. Kowalchuk, Nick Cercone:
Parallel Knowledge Discovery Using Domain Generalization Graphs. PKDD 1997: 25-35
1996
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Howard J. Hamilton, Robert J. Hilderman, Nick Cercone:
Attribute-oriented Induction Using Domain Generalization Graphs. ICTAI 1996: 246-253
1995
[c1]
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Robert J. Hilderman, Howard J. Hamilton:
Performance Analysis of a Regeneration-Based Dynamic Voting Algorithm. SRDS 1995: 196-205

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