| 2008 |
|---|
| 105 | EE | Alexandre Termier,
Marie-Christine Rousset,
Michèle Sebag,
Kouzou Ohara,
Takashi Washio,
Hiroshi Motoda:
DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm.
IEEE Trans. Knowl. Data Eng. 20(3): 300-320 (2008) |
| 104 | EE | Xindong Wu,
Vipin Kumar,
J. Ross Quinlan,
Joydeep Ghosh,
Qiang Yang,
Hiroshi Motoda,
Geoffrey J. McLachlan,
Angus Ng,
Bing Liu,
Philip S. Yu,
Zhi-Hua Zhou,
Michael Steinbach,
David J. Hand,
Dan Steinberg:
Top 10 algorithms in data mining.
Knowl. Inf. Syst. 14(1): 1-37 (2008) |
| 2007 |
|---|
| 103 | EE | Takashi Washio,
Hiroshi Motoda:
Communicability Criteria of Law Equations Discovery.
Computational Discovery of Scientific Knowledge 2007: 98-119 |
| 102 | EE | Hiroshi Motoda:
Pattern Discovery from Graph-Structured Data - A Data Mining Perspective.
IEA/AIE 2007: 12-22 |
| 101 | EE | Yang Sok Kim,
Byeong Ho Kang,
Paul Compton,
Hiroshi Motoda:
Search engine retrieval of changing information.
WWW 2007: 1195-1196 |
| 2006 |
|---|
| 100 | EE | Hiroshi Motoda:
What Can We Do with Graph-Structured Data? - A Data Mining Perspective.
Australian Conference on Artificial Intelligence 2006: 1-2 |
| 99 | EE | Kenta Fukata,
Takashi Washio,
Hiroshi Motoda:
A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis.
ICDM Workshops 2006: 590-595 |
| 98 | EE | Takashi Washio,
Yasuo Shinnou,
Katsutoshi Yada,
Hiroshi Motoda,
Takashi Okada:
Analysis on a Relation Between Enterprise Profit and Financial State by Using Data Mining Techniques.
JSAI 2006: 305-316 |
| 97 | EE | Phu Chien Nguyen,
Kouzou Ohara,
Akira Mogi,
Hiroshi Motoda,
Takashi Washio:
Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction.
PAKDD 2006: 390-399 |
| 96 | EE | Kiyoto Takabayashi,
Phu Chien Nguyen,
Kouzou Ohara,
Hiroshi Motoda,
Takashi Washio:
Extracting Discriminative Patterns from Graph Structured Data Using Constrained Search.
PKAW 2006: 64-74 |
| 95 | EE | Toshiko Wakaki,
Hiroyuki Itakura,
Masaki Tamura,
Hiroshi Motoda,
Takashi Washio:
A study on rough set-aided feature selection for automatic web-page classification.
Web Intelligence and Agent Systems 4(4): 431-441 (2006) |
| 2005 |
|---|
| 94 | | Shusaku Tsumoto,
Takahira Yamaguchi,
Masayuki Numao,
Hiroshi Motoda:
Active Mining, Second International Workshop, AM 2003, Maebashi, Japan, October 28, 2003, Revised Selected Papers
Springer 2005 |
| 93 | | Achim G. Hoffmann,
Hiroshi Motoda,
Tobias Scheffer:
Discovery Science, 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings
Springer 2005 |
| 92 | EE | Takashi Washio,
Fuminori Adachi,
Hiroshi Motoda:
SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos.
Discovery Science 2005: 253-266 |
| 91 | EE | Alexandre Termier,
Marie-Christine Rousset,
Michèle Sebag,
Kouzou Ohara,
Takashi Washio,
Hiroshi Motoda:
Efficient Mining of High Branching Factor Attribute Trees.
ICDM 2005: 785-788 |
| 90 | EE | Takashi Washio,
Yuki Mitsunaga,
Hiroshi Motoda:
Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering.
ICDM 2005: 793-796 |
| 89 | EE | Takashi Washio,
Fuminori Adachi,
Hiroshi Motoda:
Discovering Time Differential Law Equations Containing Hidden State Variables and Chaotic Dynamics.
IJCAI 2005: 1642-1644 |
| 88 | EE | Takashi Washio,
Koutarou Nakanishi,
Hiroshi Motoda,
Takashi Okada:
Mutagenicity Risk Analysis by Using Class Association Rules.
JSAI Workshops 2005: 436-445 |
| 87 | EE | Phu Chien Nguyen,
Kouzou Ohara,
Hiroshi Motoda,
Takashi Washio:
Cl-GBI: A Novel Approach for Extracting Typical Patterns from Graph-Structured Data.
PAKDD 2005: 639-649 |
| 86 | EE | Takashi Washio,
Koutarou Nakanishi,
Hiroshi Motoda:
Deriving Class Association Rules Based on Levelwise Subspace Clustering.
PKDD 2005: 692-700 |
| 85 | EE | Kenichi Yoshida,
Fuminori Adachi,
Takashi Washio,
Hiroshi Motoda,
Teruaki Homma,
Akihiro Nakashima,
Hiromitsu Fujikawa,
Katsuyuki Yamazaki:
Memory Management of Density-Based Spam Detector.
SAINT 2005: 370-376 |
| 84 | EE | Takashi Washio,
Atsushi Fujimoto,
Hiroshi Motoda:
A Framework of Numerical Basket Analysis.
SAINT Workshops 2005: 340-343 |
| 83 | EE | Warodom Geamsakul,
Tetsuya Yoshida,
Kouzou Ohara,
Hiroshi Motoda,
Hideto Yokoi,
Katsuhiko Takabayashi:
Constructing a Decision Tree for Graph-Structured Data and its Applications.
Fundam. Inform. 66(1-2): 131-160 (2005) |
| 82 | EE | Akihiro Inokuchi,
Takashi Washio,
Hiroshi Motoda:
A General Framework for Mining Frequent Subgraphs from Labeled Graphs.
Fundam. Inform. 66(1-2): 53-82 (2005) |
| 81 | EE | Takashi Washio,
Hiroshi Motoda,
Yuji Niwa:
Enhancing the plausibility of law equation discovery through cross check among multiple scale-type-based models.
J. Exp. Theor. Artif. Intell. 17(1-2): 129-143 (2005) |
| 2004 |
|---|
| 80 | EE | Kouzou Ohara,
Yukio Onishi,
Noboru Babaguchi,
Hiroshi Motoda:
Constructive Inductive Learning Based on Meta-attributes.
Discovery Science 2004: 142-154 |
| 79 | EE | Kenichi Yoshida,
Fuminori Adachi,
Takashi Washio,
Hiroshi Motoda,
Teruaki Homma,
Akihiro Nakashima,
Hiromitsu Fujikawa,
Katsuyuki Yamazaki:
Density-based spam detector.
KDD 2004: 486-493 |
| 78 | EE | Katsutoshi Yada,
Hiroshi Motoda,
Takashi Washio,
Asuka Miyawaki:
Consumer Behavior Analysis by Graph Mining Technique.
KES 2004: 800-806 |
| 77 | EE | Amit Mandvikar,
Huan Liu,
Hiroshi Motoda:
Compact Dual Ensembles for Active Learning.
PAKDD 2004: 293-297 |
| 76 | EE | Phu Chien Nguyen,
Takashi Washio,
Kouzou Ohara,
Hiroshi Motoda:
Using a Hash-Based Method for Apriori-Based Graph Mining.
PKDD 2004: 349-361 |
| 75 | EE | Huan Liu,
Hiroshi Motoda,
Lei Yu:
A selective sampling approach to active feature selection.
Artif. Intell. 159(1-2): 49-74 (2004) |
| 74 | EE | Tetsuya Yoshida,
Takuya Wada,
Hiroshi Motoda,
Takashi Washio:
Adaptive Ripple Down Rules method based on minimum description length principle.
Intell. Data Anal. 8(3): 239-265 (2004) |
| 73 | EE | Nada Lavrac,
Hiroshi Motoda,
Tom Fawcett,
Robert Holte,
Pat Langley,
Pieter W. Adriaans:
Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving.
Machine Learning 57(1-2): 13-34 (2004) |
| 72 | EE | Nada Lavrac,
Hiroshi Motoda,
Tom Fawcett:
Editorial: Data Mining Lessons Learned.
Machine Learning 57(1-2): 5-11 (2004) |
| 2003 |
|---|
| 71 | EE | Shusaku Tsumoto,
Takahira Yamaguchi,
Masayuki Numao,
Hiroshi Motoda:
Active Mining Project: Overview.
Active Mining 2003: 1-10 |
| 70 | EE | Warodom Geamsakul,
Tetsuya Yoshida,
Kouzou Ohara,
Hiroshi Motoda,
Takashi Washio,
Hideto Yokoi,
Katsuhiko Takabayashi:
Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction.
Active Mining 2003: 126-151 |
| 69 | EE | Warodom Geamsakul,
Takashi Matsuda,
Tetsuya Yoshida,
Hiroshi Motoda,
Takashi Washio:
Performance Evaluation of Decision Tree Graph-Based Induction.
Discovery Science 2003: 128-140 |
| 68 | EE | Fuminori Adachi,
Takashi Washio,
Hiroshi Motoda,
Atsushi Fujimoto,
Hidemitsu Hanafusa:
Development of Generic Search Method Based on Transformation Invariance.
ISMIS 2003: 486-495 |
| 67 | EE | Huan Liu,
Lei Yu,
Manoranjan Dash,
Hiroshi Motoda:
Active Feature Selection Using Classes.
PAKDD 2003: 474-485 |
| 66 | EE | Warodom Geamsakul,
Takashi Matsuda,
Tetsuya Yoshida,
Hiroshi Motoda,
Takashi Washio:
Classifier Construction by Graph-Based Induction for Graph-Structured Data.
PAKDD 2003: 52-62 |
| 65 | | Akihiro Inokuchi,
Takashi Washio,
Hiroshi Motoda:
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data.
Machine Learning 50(3): 321-354 (2003) |
| 64 | EE | Takashi Washio,
Hiroshi Motoda:
State of the art of graph-based data mining.
SIGKDD Explorations 5(1): 59-68 (2003) |
| 63 | | Setsuo Arikawa,
Koichi Furukawa,
Shinichi Morishita,
Hiroshi Motoda:
Preface.
Theor. Comput. Sci. 292(2): 343-344 (2003) |
| 2002 |
|---|
| 62 | EE | Takashi Matsuda,
Hiroshi Motoda,
Tetsuya Yoshida,
Takashi Washio:
Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction.
Discovery Science 2002: 422-429 |
| 61 | EE | Tetsuya Yoshida,
Hiroshi Motoda,
Takashi Washio:
Adaptive Ripple Down Rules Method based on Minimum Description Length Principle.
ICDM 2002: 530-537 |
| 60 | | Huan Liu,
Hiroshi Motoda,
Lei Yu:
Feature Selection with Selective Sampling.
ICML 2002: 395-402 |
| 59 | EE | Takuya Wada,
Tetsuya Yoshida,
Hiroshi Motoda,
Takashi Washio:
Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data.
PRICAI 2002: 218-227 |
| 58 | EE | Keisei Fujiwara,
Tetsuya Yoshida,
Hiroshi Motoda,
Takashi Washio:
Case Generation Method for Constructing an RDR Knowledge Base.
PRICAI 2002: 228-237 |
| 57 | EE | Takashi Matsuda,
Hiroshi Motoda,
Tetsuya Yoshida,
Takashi Washio:
Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction.
PRICAI 2002: 255-264 |
| 56 | EE | Takashi Washio,
Hiroshi Motoda:
Toward the Discovery of First Principle Based Scientific Law Equations.
Progress in Discovery Science 2002: 553-564 |
| 55 | EE | Takashi Matsuda,
Hiroshi Motoda,
Takashi Washio:
Graph-based induction and its applications.
Advanced Engineering Informatics 16(2): 135-143 (2002) |
| 54 | | Huan Liu,
Hiroshi Motoda:
On Issues of Instance Selection.
Data Min. Knowl. Discov. 6(2): 115-130 (2002) |
| 53 | EE | Masahiro Terabe,
Takashi Washio,
Hiroshi Motoda,
Osamu Katai,
Tetsuo Sawaragi:
Attribute Generation Based on Association Rules.
Knowl. Inf. Syst. 4(3): 329-349 (2002) |
| 2001 |
|---|
| 52 | EE | Takashi Washio,
Hiroshi Motoda,
Yuji Niwa:
Discovering Admissible Simultaneous Equation Models from Observed Data.
ECML 2001: 539-551 |
| 51 | EE | Masahiro Terabe,
Takashi Washio,
Hiroshi Motoda:
S3Bagging: Fast Classifier Induction Method with Subsampling and Bagging.
IDA 2001: 177-186 |
| 50 | EE | Takayuki Ikeda,
Takashi Washio,
Hiroshi Motoda:
Basket Analysis on Meningitis Data.
JSAI Workshops 2001: 516-524 |
| 49 | EE | Takuya Wada,
Hiroshi Motoda,
Takashi Washio:
Knowledge Acquisition from Both Human Expert and Data.
PAKDD 2001: 550-561 |
| 48 | EE | Makoto Tsukada,
Takashi Washio,
Hiroshi Motoda:
Automatic Web-Page Classification by Using Machine Learning Methods.
Web Intelligence 2001: 303-313 |
| 47 | EE | Takuya Wada,
Tadashi Horiuchi,
Hiroshi Motoda,
Takashi Washio:
A Description Length-Based Decision Criterion for Default Knowledge in the Ripple Down Rules Method.
Knowl. Inf. Syst. 3(2): 146-167 (2001) |
| 2000 |
|---|
| 46 | EE | Takashi Matsuda,
Tadashi Horiuchi,
Hiroshi Motoda,
Takashi Washio:
Graph-Based Induction for General Graph Structured Data and Its Application to Chemical Compound Data.
Discovery Science 2000: 99-111 |
| 45 | | Takashi Washio,
Hiroshi Motoda,
Yuji Niwa:
Enhancing the Plausibility of Law Equation Discovery.
ICML 2000: 1127-1134 |
| 44 | | Takashi Matsuda,
Tadashi Horiuchi,
Hiroshi Motoda,
Takashi Washio:
Extension of Graph-Based Induction for General Graph Structured Data.
PAKDD 2000: 420-431 |
| 43 | | Manoranjan Dash,
Huan Liu,
Hiroshi Motoda:
Consistency Based Feature Selection.
PAKDD 2000: 98-109 |
| 42 | EE | Akihiro Inokuchi,
Takashi Washio,
Hiroshi Motoda:
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data.
PKDD 2000: 13-23 |
| 41 | | Hiroshi Motoda,
Setsuo Arikawa:
Special Feature on Discovery Science.
New Generation Comput. 18(1): 13-16 (2000) |
| 1999 |
|---|
| 40 | EE | Manoranjan Dash,
Huan Liu,
Hiroshi Motoda:
Feature Selection Using Consistency Measure.
Discovery Science 1999: 319-320 |
| 39 | EE | Akihiro Inokuchi,
Takashi Washio,
Hiroshi Motoda:
Derivation of the Topology Structure from Massive Graph Data.
Discovery Science 1999: 330-332 |
| 38 | EE | Takashi Matsuda,
Tadashi Horiuchi,
Hiroshi Motoda,
Takashi Washio,
Kohei Kumazawa,
Naohide Arai:
Graph-Based Induction for General Graph Structured Data.
Discovery Science 1999: 340-342 |
| 37 | | Takashi Washio,
Hiroshi Motoda,
Niwa Yuji:
Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains.
IJCAI 1999: 772-779 |
| 36 | EE | Masahiro Terabe,
Osamu Katai,
Tetsuo Sawaragi,
Takashi Washio,
Hiroshi Motoda:
A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree.
PAKDD 1999: 143-147 |
| 35 | EE | Hiroshi Motoda:
Computer Assisted Discovery of First Principle Equations from Numeric Data (Abstract).
PAKDD 1999: 2 |
| 34 | EE | Takuya Wada,
Tadashi Horiuchi,
Hiroshi Motoda,
Takashi Washio:
Characterization of Default Knowledge in Ripple Down Rules Method.
PAKDD 1999: 284-295 |
| 33 | EE | Akihiro Inokuchi,
Takashi Washio,
Hiroshi Motoda,
Kouhei Kumasawa,
Naohide Arai:
Basket Analysis for Graph Structured Data.
PAKDD 1999: 420-431 |
| 1998 |
|---|
| 32 | | Hing-Yan Lee,
Hiroshi Motoda:
PRICAI'98, Topics in Artificial Intelligence, 5th Pacific Rim International Conference on Artificial Intelligence, Singapore, November 22-27, 1998, Proceedings
Springer 1998 |
| 31 | | Setsuo Arikawa,
Hiroshi Motoda:
Discovery Science, First International Conference, DS '98, Fukuoka, Japan, December 14-16, 1998, Proceedings
Springer 1998 |
| 30 | | Takashi Washio,
Hiroshi Motoda:
Discovering Admissible Simultaneous Equations of Large Scale Systems.
AAAI/IAAI 1998: 189-196 |
| 29 | EE | Takashi Washio,
Hiroshi Motoda:
Development of SDS2: Smart Discovery System for Simultaneous Equation Systems.
Discovery Science 1998: 352-363 |
| 28 | | Huan Liu,
Hiroshi Motoda,
Manoranjan Dash:
A Monotonic Measure for Optimal Feature Selection.
ECML 1998: 101-106 |
| 27 | | Takashi Washio,
Hiroshi Motoda:
Mining Association Rules for Estimation and Prediction.
PAKDD 1998: 417-419 |
| 26 | EE | Hiroshi Motoda,
Kenichi Yoshida:
Machine Learning Techniques to Make Computers Easier to Use.
Artif. Intell. 103(1-2): 295-321 (1998) |
| 25 | | Huan Liu,
Hiroshi Motoda:
Guest Editors' Introduction: Feature Transformation and Subset Selection.
IEEE Intelligent Systems 13(2): 26-28 (1998) |
| 24 | EE | Hing-Yan Lee,
Hongjun Lu,
Hiroshi Motoda:
Knowledge discovery and data mining.
Knowl.-Based Syst. 10(7): 401-402 (1998) |
| 23 | EE | Takashi Washio,
Hiroshi Motoda:
Discovery of first-principle equations based on scale-type-based and data-driven reasoning.
Knowl.-Based Syst. 10(7): 403-411 (1998) |
| 1997 |
|---|
| 22 | | Hiroshi Motoda,
Kenichi Yoshida:
Machine Learning Techniques to Make Computers Easier to Use.
IJCAI 1997: 1622-1631 |
| 21 | | Takashi Washio,
Hiroshi Motoda:
Discovering Admissible Models of Complex Systems Based on Scale-Types and Idemtity Constraints.
IJCAI (2) 1997: 810-819 |
| 20 | EE | Byeong Ho Kang,
Kenichi Yoshida,
Hiroshi Motoda,
Paul Compton:
Help Desk System with Intelligent Interface.
Applied Artificial Intelligence 11(7-8): 611-631 (1997) |
| 1996 |
|---|
| 19 | | Takashi Washio,
Hiroshi Motoda:
A History-Oriented Envisioning Method.
PRICAI 1996: 312-323 |
| 18 | | Shingo Nishioka,
Atsuo Kawaguchi,
Hiroshi Motoda:
Process Labeled Kernel Profiling: A New Facility to Profile System Activities.
USENIX Annual Technical Conference 1996: 295-306 |
| 1995 |
|---|
| 17 | | Kenichi Yoshida,
Hiroshi Motoda:
Tables, Graphs and Logic for Induction.
Machine Intelligence 15 1995: 298-311 |
| 16 | | Atsuo Kawaguchi,
Shingo Nishioka,
Hiroshi Motoda:
A Flash-Memory Based File System.
USENIX Winter 1995: 155-164 |
| 15 | EE | Kenichi Yoshida,
Hiroshi Motoda:
CLIP: Concept Learning from Inference Patterns.
Artif. Intell. 75(1): 63-92 (1995) |
| 14 | EE | Riichiro Mizoguchi,
Hiroshi Motoda:
Expert Systems Research in Japan.
IEEE Expert 10(4): 14-23 (1995) |
| 1994 |
|---|
| 13 | | N. Hari Narayanan,
Masaki Suwa,
Hiroshi Motoda:
How Things Appear to Work: Predicting Behaviors from Device Diagrams.
AAAI 1994: 1161-1167 |
| 12 | | Masaki Suwa,
Hiroshi Motoda:
Learning Perceptually Chunked Macro Operators.
Machine Intelligence 13 1994: 419-440 |
| 11 | | Masaki Suwa,
Hiroshi Motoda:
PCLEARN: A Computer Model for Learning Perceptual Chunks.
AI Commun. 7(2): 114-125 (1994) |
| 1993 |
|---|
| 10 | | Makoto Iwayama,
Nitin Indurkhya,
Hiroshi Motoda:
A New Algorithm for Automatic Configuration of Hidden Markov Models.
ALT 1993: 237-250 |
| 9 | | Kenichi Yoshida,
Hiroshi Motoda,
Nitin Indurkhya:
Unifying Learning Methods by Colored Digraphs.
ALT 1993: 342-355 |
| 8 | | Masaki Suwa,
Hiroshi Motoda:
A Perceptual Criterion for Visually Controlling Learning.
ALT 1993: 356-369 |
| 7 | | Masaki Suwa,
Hiroshi Motoda:
On dealing with dynamic utility of learned knowledge.
Machine Intelligence 14 1993: 113- |
| 1991 |
|---|
| 6 | EE | Hiroshi Motoda,
Riichiro Mizoguchi,
John H. Boose,
Brian R. Gaines:
Knowledge Acquisition for Knowledge-Based Systems.
IEEE Expert 6(4): 53-64 (1991) |
| 5 | EE | Atsuo Kawaguchi,
Hiroshi Motoda,
Riichiro Mizoguchi:
Interview-Based Knowledge Acquisition Using Dynamic Analysis.
IEEE Expert 6(5): 47-60 (1991) |
| 1990 |
|---|
| 4 | EE | Hiroshi Motoda:
The Current Status of Expert System Development and Related Technologies in Japan.
IEEE Expert 5(4): 3-11 (1990) |
| 1988 |
|---|
| 3 | | Akito Sakurai,
Hiroshi Motoda:
Proving Definite Clauses without Explicit Use of Inductions.
LP 1988: 11-26 |
| 1984 |
|---|
| 2 | | Hiroshi Motoda,
Naoyuki Yamada,
Kenichi Yoshida:
A Knowledge based System for Plant Diagnosis.
FGCS 1984: 582-588 |
| 1983 |
|---|
| 1 | | Naoyuki Yamada,
Hiroshi Motoda:
A Diagnosis Method of Dynamic System Using the Knowledge on System Description.
IJCAI 1983: 225-229 |
