Hiroshi Motoda Papers on DiSC'03 Adaptive Ripple Down Rules Method based on Minimum Description Length Principle Publications Note: Links lead to the DBLP on the Web. Hiroshi Motoda 58 Huan Liu , Lei Yu , Manoranjan Dash , Hiroshi Motoda: Active Feature Selection Using Classes. PAKDD 2003 : 474-485 57 Warodom Geamsakul , Takashi Matsuda , Tetsuya Yoshida , Hiroshi Motoda, Takashi Washio : Classifier Construction by Graph-Based Induction for Graph-Structured Data. PAKDD 2003 : 52-62 56 Akihiro Inokuchi , Takashi Washio , Hiroshi Motoda: Complete Mining of Frequent Patterns from Graphs: Mining Graph Data. Machine Learning 50 (3): 321-354 (2003) 55 Setsuo Arikawa , Koichi Furukawa , Shinichi Morishita , Hiroshi Motoda: Preface. TCS 292 (2): 343-344 (2003) 54 Takashi Matsuda , Hiroshi Motoda, Tetsuya Yoshida , Takashi Washio : Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction. Discovery Science 2002 : 422-429 53 Tetsuya Yoshida , Hiroshi Motoda, Takashi Washio : Adaptive Ripple Down Rules Method based on Minimum Description Length Principle. ICDM 2002 : 530-537 52 Huan Liu , Hiroshi Motoda, Lei Yu : Feature Selection with Selective Sampling. ICML 2002 : 395-402 51 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 50 Keisei Fujiwara , Tetsuya Yoshida , Hiroshi Motoda, Takashi Washio : Case Generation Method for Constructing an RDR Knowledge Base. PRICAI 2002 : 228-237 49 Takashi Matsuda , Hiroshi Motoda, Tetsuya Yoshida , Takashi Washio : Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction. PRICAI 2002 : 255-264 48 Takashi Washio , Hiroshi Motoda: Toward the Discovery of First Principle Based Scientific Law Equations. Progress in Discovery Science 2002 : 553-564 47 Huan Liu , Hiroshi Motoda: On Issues of Instance Selection. Data Mining and Knowledge Discovery 6 (2): 115-130 (2002) 46 Masahiro Terabe , Takashi Washio , Hiroshi Motoda, Osamu Katai , Tetsuo Sawaragi : Attribute Generation Based on Association Rules. Knowledge and Information Systems 4 (3): 329-349 (2002) 45 Takashi Washio , Hiroshi Motoda, Yuji Niwa : Discovering Admissible Simultaneous Equation Models from Observed Data. ECML 2001 : 539-551 44 Masahiro Terabe , Takashi Washio , Hiroshi Motoda: S 3 Bagging: Fast Classifier Induction Method with Subsampling and Bagging. IDA 2001 : 177-186 43 Takayuki Ikeda , Takashi Washio , Hiroshi Motoda: Basket Analysis on Meningitis Data. JSAI Workshops 2001 : 516-524 42 Takuya Wada , Hiroshi Motoda, Takashi Washio : Knowledge Acquisition from Both Human Expert and Data. PAKDD 2001 : 550-561 41 Makoto Tsukada , Takashi Washio , Hiroshi Motoda: Automatic Web-Page Classification by Using Machine Learning Methods. Web Intelligence 2001 : 303-313 40 Takuya Wada , Tadashi Horiuchi , Hiroshi Motoda, Takashi Washio : A Description Length-Based Decision Criterion for Default Knowledge in the Ripple Down Rules Method. Knowledge and Information Systems 3 (2): 146-167 (2001) 39 Takashi Washio , Hiroshi Motoda, Yuji Niwa : Enhancing the Plausibility of Law Equation Discovery. ICML 2000 : 1127-1134 38 Takashi Matsuda , Tadashi Horiuchi , Hiroshi Motoda, Takashi Washio : Extension of Graph-Based Induction for General Graph Structured Data. PAKDD 2000 : 420-431 37 Manoranjan Dash , Huan Liu , Hiroshi Motoda: Consistency Based Feature Selection. PAKDD 2000 : 98-109 36 Akihiro Inokuchi , Takashi Washio , Hiroshi Motoda: An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data. PKDD 2000 : 13-23 35 Hiroshi Motoda, Setsuo Arikawa : Special Feature on Discovery Science. New Generation Computing 18 (1): 13-16 (2000) 34 Manoranjan Dash , Huan Liu , Hiroshi Motoda: Feature Selection Using Consistency Measure. Discovery Science 1999 : 319-320 33 Akihiro Inokuchi , Takashi Washio , Hiroshi Motoda: Derivation of the Topology Structure from Massive Graph Data. Discovery Science 1999 : 330-332 32 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 31 Takashi Washio , Hiroshi Motoda, Niwa Yuji : Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains. IJCAI 1999 : 772-779 30 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 29 Hiroshi Motoda: Computer Assisted Discovery of First Principle Equations from Numeric Data (Abstract). PAKDD 1999 : 2 28 Takuya Wada , Tadashi Horiuchi , Hiroshi Motoda, Takashi Washio : Characterization of Default Knowledge in Ripple Down Rules Method. PAKDD 1999 : 284-295 27 Akihiro Inokuchi , Takashi Washio , Hiroshi Motoda, Kouhei Kumasawa , Naohide Arai : Basket Analysis for Graph Structured Data. PAKDD 1999 : 420-431 26 Setsuo Arikawa , Hiroshi Motoda: Discovery Science, First International Conference, DS '98, Fukuoka, Japan, December 14-16, 1998, Proceedings. Springer 1998 25 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 24 Takashi Washio , Hiroshi Motoda: Discovering Admissible Simultaneous Equations of Large Scale Systems. AAAI/IAAI 1998 : 189-196 23 Takashi Washio , Hiroshi Motoda: Development of SDS2: Smart Discovery System for Simultaneous Equation Systems. Discovery Science 1998 : 352-363 22 Huan Liu , Hiroshi Motoda, Manoranjan Dash : A Monotonic Measure for Optimal Feature Selection. ECML 1998 : 101-106 21 Takashi Washio , Hiroshi Motoda: Mining Association Rules for Estimation and Prediction. PAKDD 1998 : 417-419 20 Hiroshi Motoda, Kenichi Yoshida : Machine Learning Techniques to Make Computers Easier to Use. Artificial Intelligence 103 (1-2): 295-321 (1998) 19 Huan Liu , Hiroshi Motoda: Guest Editors' Introduction: Feature Transformation and Subset Selection. IEEE Intelligent Systems 13 (2): 26-28 (1998) 18 Hiroshi Motoda, Kenichi Yoshida : Machine Learning Techniques to Make Computers Easier to Use. IJCAI 1997 : 1622-1631 17 Takashi Washio , Hiroshi Motoda: Discovering Admissible Models of Complex Systems Based on Scale-Types and Idemtity Constraints. IJCAI (2) 1997 : 810-819 16 Takashi Washio , Hiroshi Motoda: A History-Oriented Envisioning Method. PRICAI 1996 : 312-323 15 Shingo Nishioka , Atsuo Kawaguchi , Hiroshi Motoda: Process Labeled Kernel Profiling: A New Facility to Profile System Activities. USENIX Annual Technical Conference 1996 : 295-306 14 Kenichi Yoshida , Hiroshi Motoda: Tables, Graphs and Logic for Induction. Machine Intelligence 15 1995 : 298-311 13 Atsuo Kawaguchi , Shingo Nishioka , Hiroshi Motoda: A Flash-Memory Based File System. USENIX Winter 1995 : 155-164 12 Kenichi Yoshida , Hiroshi Motoda: CLIP: Concept Learning from Inference Patterns. Artificial Intelligence 75 (1): 63-92 (1995) 11 Riichiro Mizoguchi , Hiroshi Motoda: Expert Systems Research in Japan. IEEE Expert 10 (3): 14-23 (1995) 10 N. Hari Narayanan , Masaki Suwa , Hiroshi Motoda: How Things Appear to Work: Predicting Behaviors from Device Diagrams. AAAI 1994 : 1161-1167 9 Masaki Suwa , Hiroshi Motoda: Learning Perceptually Chunked Macro Operators. Machine Intelligence 13 1994 : 419-440 8 Masaki Sssuwa , Hiroshi Motoda: PCLEARN: A Computer Model for Learning Perceptual Chunks. AI Communications 7 (2): 114-125 (1994) 7 Makoto Iwayama , Nitin Indurkhya , Hiroshi Motoda: A New Algorithm for Automatic Configuration of Hidden Markov Models. ALT 1993 : 237-250 6 Kenichi Yoshida , Hiroshi Motoda, Nitin Indurkhya : Unifying Learning Methods by Colored Digraphs. ALT 1993 : 342-355 5 Masaki Suwa , Hiroshi Motoda: A Perceptual Criterion for Visually Controlling Learning. ALT 1993 : 356-369 4 Masaki Suwa , Hiroshi Motoda: On dealing with dynamic utility of learned knowledge. Machine Intelligence 14 1993 : 113- 3 Akito Sakurai , Hiroshi Motoda: Proving Definite Clauses without Explicit Use of Inductions. LP 1988 : 11-26 2 Hiroshi Motoda, Naoyuki Yamada , Kenichi Yoshida : A Knowledge based System for Plant Diagnosis. FGCS 1984 : 582-588 1 Naoyuki Yamada , Hiroshi Motoda: A Diagnosis Method of Dynamic System Using the Knowledge on System Description. IJCAI 1983 : 225-229 DiSC'03 © 2003 Association for Computing Machinery