Hidenao Abe

	2011
61		Hidenao Abe, Shusaku Tsumoto: Constructing features for document classification by using temporal patterns of term usages. GrC 2011: 30-36
60		Hidenao Abe, Shusaku Tsumoto: Mining Classification Rules for Detecting Medication Order Changes by Using Characteristic CPOE Subsequences. ISMIS 2011: 80-89
59		Hidenao Abe, Shusaku Tsumoto: Comparing a Clustering Density Criteria of Temporal Patterns of Terms Obtained by Different Feature Sets. RSKT 2011: 248-257
58		Shusaku Tsumoto, Shoji Hirano, Hidenao Abe, Yuko Tsumoto: Temporal data mining in history data of hospital information systems. SMC 2011: 2350-2356
57		Hidenao Abe, Shusaku Tsumoto: Evaluating a Temporal Pattern Detection Method for Finding Research Keys in Bibliographical Data. T. Rough Sets 14: 1-17 (2011)
	2010
56		Hidenao Abe, Shusaku Tsumoto: Analysis of Research Keys as Tempral Patterns of Technical Term Usages in Bibliographical Data. AMT 2010: 150-157
55		Hidenao Abe, Shusaku Tsumoto: Text Categorization with Considering Temporal Patterns of Term Usages. ICDM Workshops 2010: 800-807
54		Hidenao Abe, Shusaku Tsumoto: Comparing order entry subsequences related to CPOE correction factors. IEEE ICCI 2010: 806-810
53		Hidenao Abe, Shusaku Tsumoto: Mining Temporal Patterns of Technical Term Usages in Bibliographical Data. Intelligent Information Processing 2010: 130-138
52		Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Automated Empirical Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods. Intelligent Information Processing 2010: 139-144
51		Hidenao Abe, Shusaku Tsumoto: Discovering Research Key Terms as Temporal Patterns of Importance Indices for Text Mining. KES (3) 2010: 297-306
50		Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Likelihood-Based Sampling from Databases for Rule Induction Methods. RSKT 2010: 265-272
49		Hidenao Abe, Shusaku Tsumoto: Trend detection from large text data. SMC 2010: 310-315
	2009
48		Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Multivariate statistical independence and contingency tables. GrC 2009: 544-548
47		Hidenao Abe, Shusaku Tsumoto: Detection of trends of technical phrases in text mining. GrC 2009: 7-12
46		Hidenao Abe, Shusaku Tsumoto: Detecting Similarity of Transferring Datasets Based on Features of Classification Rules. ICDM Workshops 2009: 412-415
45		Hidenao Abe, Shusaku Tsumoto: Evaluating a method to detect temporal trends of phrases in research documents. IEEE ICCI 2009: 378-383
44		Hidenao Abe, Shusaku Tsumoto: Detecting Temporal Trends of Technical Phrases by Using Importance Indices and Linear Regression. ISMIS 2009: 251-260
43		Shusaku Tsumoto, Hidenao Abe: Evaluation of a Classification Rule Mining Algorithm Based on Secondary Differences. KES (2) 2009: 24-31
42		Hidenao Abe, Shusaku Tsumoto: Detecting Temporal Patterns of Importance Indices about Technical Phrases. KES (2) 2009: 252-258
41		Hidenao Abe, Shusaku Tsumoto: Comparing Temporal Behavior of Phrases on Multiple Indexes with a Burst Word Detection Method. RSFDGrC 2009: 502-509
40		Hidenao Abe, Shusaku Tsumoto: A Comparison of Composed Objective Rule Evaluation Indices Using PCA and Single Indices. RSKT 2009: 160-167
39		Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Pearson Residuals in Multi-way Contingency Tables. SMC 2009: 2531-2536
38		Hidenao Abe, Shusaku Tsumoto: Detecting Temporal Patterns of Technical Phrases by using Importance Indices in a Research Documents. SMC 2009: 2959-2964
37		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method. Mining Complex Data 2009: 95-111
36		Hidenao Abe, Shusaku Tsumoto: Investigating Accuracies of Classifications for Randomized Imbalanced Class Distributions. Fundam. Inform. 90(4): 369-378 (2009)
	2008
35		Hidenao Abe, Shusaku Tsumoto: Investigating Accuracies of Rule Evaluation Models on Randomized Labeling and Human Evaluation. GrC 2008: 95-100
34		Hidenao Abe, Shusaku Tsumoto: Comparing Accuracies of Rule Evaluation Models to Determine Human Criteria on Evaluated Rule Sets. ICDM Workshops 2008: 1-7
33		Hidenao Abe, Shusaku Tsumoto: Analyzing Behavior of Objective Rule Evaluation Indices Based on Pearson Product-Moment Correlation Coefficient. ISMIS 2008: 84-89
32		Hidenao Abe, Shusaku Tsumoto: Analyzing Behavior of Objective Rule Evaluation Indices Based on a Correlation Coefficient. KES (2) 2008: 758-765
31		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Finding Functional Groups of Objective Rule Evaluation Indices Using PCA. PAKM 2008: 197-206
30		Hidenao Abe, Shusaku Tsumoto: Implementing a Rule Generation Method Based on Secondary Differences of Two Criteria. RSCTC 2008: 293-298
29		Hidenao Abe, Shusaku Tsumoto: Analyzing Correlation Coefficients of Objective Rule Evaluation Indices on Classification Rules. RSKT 2008: 467-474
28		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices. Communications and Discoveries from Multidisciplinary Data 2008: 269-282
	2007
27		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi: Evaluation of Learning Costs of Rule Evaluation Models Based on Objective Indices to Predict Human Hypothesis Construction Phases. GrC 2007: 458-464
26		Hidenao Abe, Hideto Yokoi, Miho Ohsaki, Takahira Yamaguchi: Developing an Integrated Time-Series Data Mining Environment for Medical Data Mining. ICDM Workshops 2007: 127-132
25		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices. IEEE ICCI 2007: 212-221
24		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating a Constructive Meta-learning Algorithm for a Rule Evaluation Support Method Based on Objective Indices. KES (2) 2007: 934-941
23		Hidenao Abe, Satoru Hirabayashi, Miho Ohsaki, Takahira Yamaguchi: Evaluating Accuracies of a Trading Rule Mining Method Based on Temporal Pattern Extraction. MCD 2007: 72-81
22		Hidenao Abe, Hideto Yokoi, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Models with Transitions of Human Interests Based on Objective Rule Evaluation Indices. MedInfo 2007: 581-585
21		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating learning algorithms for a rule evaluation support method. SMC 2007: 3784-3789
20		Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi: Evaluation of rule interestingness measures in medical knowledge discovery in databases. Artificial Intelligence in Medicine 41(3): 177-196 (2007)
19		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms to Support Human Rule - Evaluation Based on Objective Rule Evaluation Indices. Data Science Journal 6: 285-296 (2007)
18		Miho Ohsaki, Hidenao Abe, Takahira Yamaguchi: Numerical Time-Series Pattern Extraction Based on Irregular Piecewise Aggregate Approximation and Gradient Specification. New Generation Comput. 25(3): 213-222 (2007)
	2006
17		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms Composed by a Constructive Meta-Learning Scheme for a Rule Evaluation Support Method. ICDM Workshops 2006: 305-310
16		Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi: Proposal of Medical KDD Support User Interface Utilizing Rule Interestingness Measures. ICDM Workshops 2006: 759-764
15		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms for a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. ISMIS 2006: 379-388
14		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Model Construction Methods with Objective Rule Evaluation Indices to Support Human Experts. MDAI 2006: 93-104
13		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. PAKDD 2006: 509-519
12		Hidenao Abe, Takahira Yamaguchi: Constructive Meta-level Feature Selection Method Based on Method Repositories. PAKDD 2006: 70-80
11		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi: Evaluating Learning Algorithms with Meta-learning Schemes for a Rule Evaluation Support Method Based on Objective Indices. PKAW 2006: 75-88
10		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Models for a Rule Evaluation Support Method Based on Objective Indices. RSCTC 2006: 687-695
9		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Developing a Rule Evaluation Support Method Based on Objective Indices. RSKT 2006: 456-461
8		Hidenao Abe, Takahira Yamaguchi: A Constructive Meta-Level Feature Selection Method based on Method Repositories. JCP 1(3): 20-26 (2006)
	2005
7		Hidenao Abe, Miho Ohsaki, Shusaku Tsumoto, Takahira Yamaguchi: Evaluating a Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indices - A Case Study with a Meningitis Data Mining Result. HIS 2005: 169-174
6		Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes. ICDM 2005: 549-552
5		Hidenao Abe, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi: Implementing an Integrated Time-Series Data Mining Environment Based on Temporal Pattern Extraction Methods: A Case Study of an Interferon Therapy Risk Mining for Chronic Hepatitis. JSAI Workshops 2005: 425-435
4		Shusaku Tsumoto, Shoji Hirano, Hidenao Abe, Hideaki Nakakuni, Eisuke Hanada: Clinical Decision Support Based on Mobile Telecommunication Systems. Web Intelligence 2005: 700-703
	2004
3		Hidenao Abe, Takahira Yamaguchi: Constructive Meta-learning with Machine Learning Method Repositories. IEA/AIE 2004: 502-511
	2002
2		Hidenao Abe, Takahira Yamaguchi: Constructing Inductive Applications by Meta-Learning with Method Repositories. Progress in Discovery Science 2002: 576-585
	2001
1		Hiromitsu Hatazawa, Hidenao Abe, Mao Komori, Yoshiaki Tachibana, Takahira Yamaguchi: Knowledge Discovery Support from a Meningoencephalitis Dataset Using an Automatic Composition Tool for Inductive Applications. JSAI Workshops 2001: 500-507

Coauthor Index

1	Eisuke Hanada	[4]
2	Hiromitsu Hatazawa	[1]
3	Satoru Hirabayashi	[23]
4	Shoji Hirano	[4] [39] [48] [50] [52] [58]
5	Mao Komori	[1]
6	Hideaki Nakakuni	[4]
7	Miho Ohsaki	[5] [6] [7] [9] [10] [11] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [31] [37]
8	Yoshiaki Tachibana	[1]
9	Shusaku Tsumoto	[4] [6] [7] [9] [10] [11] [13] [14] [15] [16] [17] [19] [20] [21] [22] [24] [25] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61]
10	Yuko Tsumoto	[58]
11	Takahira Yamaguchi	[1] [2] [3] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [31] [37]
12	Hideto Yokoi	[5] [11] [16] [20] [22] [26] [27]

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