Hiroshi Motoda

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Data Processing and Knowledge Discovery in Databases

Hiroshi Motoda, Huan Liu, H. Motoda, 1998 .

A Diagnosis Method of Dynamic System Using the Knowledge on System Description

Hiroshi Motoda, Naoyuki Yamada, 1983, IJCAI.

Proceedings of the First International Conference on Discovery Science

Setsuo Arikawa, Hiroshi Motoda, H. Motoda, 1998 .

Feature Selection Methods

Hiroshi Motoda, Huan Liu, H. Motoda, 1998 .

What Does an Information Diffusion Model Tell about Social Network Structure?

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2008, PKAW.

Learning Information Diffusion Model for Extracting Influential Nodes in a Social Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010 .

Learning information diffusion model in a social network for predicting influence of nodes

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2011, Intell. Data Anal..

Top 10 algorithms in data mining

Philip S. Yu, Xindong Wu, Qiang Yang, 2007, Knowledge and Information Systems.

Advanced Data Mining and Applications

Zhaohui Wu, Longbing Cao, Hiroshi Motoda, 2013, Lecture Notes in Computer Science.

Cl-GBI : A Novel Strategy to Extract Typical Patterns from Graph Data(Graph Data Mining)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2004 .

CLIP: Concept Learning from Inference Patterns

Hiroshi Motoda, Kenichi Yoshida, H. Motoda, 1995, Artif. Intell..

Generalization for Frequent Subgraph Mining

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 2004 .

Graph-based induction as a unified learning framework

Hiroshi Motoda, Kenichi Yoshida, Nitin Indurkhya, 1994, Applied Intelligence.

Mining Quantitative Frequent Itemsets Using Adaptive Density-based Subspace Clustering

Takashi Washio, Hiroshi Motoda, Yuki Mitsunaga, 2006 .

A New Approach for Item Ranking Based on Review Scores Reflecting Temporal Trust Factor

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2014, SBP.

Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2009, ACML.

Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving

Nada Lavrac, Pat Langley, Hiroshi Motoda, 2004, Machine Learning.

Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2003, Active Mining.

Multi-structure information retrieval method based on transformation invariance

Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, 2005, New Generation Computing.

How Things Appear to Work: Predicting Behaviors from Device Diagrams

Masaki Suwa, N. Hari Narayanan, Hiroshi Motoda, 1994, AAAI.

Relevance Reasoning to Guide Compositional Modeling

Hiroshi Motoda, Yumi Iwasaki, Alon Y. Levy, 2004 .

Discovering Influential Nodes for SIS Models in Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2009, Discovery Science.

A History-Oriented Envisioning Method

Takashi Washio, Hiroshi Motoda, 1996, PRICAI.

Behavior and Social Computing

Philip S. Yu, Guandong Xu, Longbing Cao, 2013, Lecture Notes in Computer Science.

Cl-GBI: A Novel Strategy to Extract Typical Patterns from Graph Data (Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining) -- (Session 4: Web Data Mining)

Hiroshi Motoda, Kouzou Ohara, Phu Chien Nguyen, 2004 .

Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2020, DS.

Machine Learning Techniques to Make Computers Easier to Use

Hiroshi Motoda, Kenichi Yoshida, H. Motoda, 1997, IJCAI.

Acquisition of associative knowledge by the frustration-based learning method in an auxiliary-line problem

Hiroshi Motoda, M. Suwa, 1989 .

| Computational Methods of Feature Selection | Taylor & Francis Group

Hiroshi Motoda, Huan Liu, H. Motoda, 2007 .

A New Algorithm for Automatic Configuration of Hidden Markov Models

Makoto Iwayama, Hiroshi Motoda, Nitin Indurkhya, 1993, ALT.

Development of Generic Search Method Based on Transformation Invariance

Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, 2003, ISMIS.

Graph-Based Induction for General Graph Structured Data

Tadashi Horiuchi, Takashi Washio, Hiroshi Motoda, 1999, IFIP Working Conference on Database Semantics.

A selective sampling approach to active feature selection

Huan Liu, Lei Yu, Hiroshi Motoda, 2004, Artif. Intell..

Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2015, PAKDD.

Analysis on a Relation Between Enterprise Profit and Financial State by Using Data Mining Techniques

Katsutoshi Yada, Takashi Washio, Hiroshi Motoda, 2006, JSAI.

Method for extracting connected frequent subgraphs in Graph Structured Data

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 2002 .

Case Generation Method for Constructing an RDR Knowledge Base

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002, PRICAI.

Computer program for control rod programming of BWR

Hiroshi Motoda, Takashi Kiguchi, Toshio Kawai, 1973 .

Change Point Detection for Information Diffusion Tree

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2015, Discovery Science.

Discovering Admissible Models of Complex Systems Based on Scale-Types and Idemtity Constraints

Takashi Washio, Hiroshi Motoda, T. Washio, 1997, IJCAI.

Book Review: Computational Methods of Feature Selection

Hiroshi Motoda, Huan Liu, Huan Liu, 2007, The IEEE intelligent informatics bulletin.

Learning Perceptually Chunked Macro Operators

Masaki Suwa, Hiroshi Motoda, M. Suwa, 1994, Machine Intelligence 13.

Accurate and efficient detection of critical links in network to minimize information loss

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2018, Journal of Intelligent Information Systems.

A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis

Takashi Washio, Hiroshi Motoda, Kenta Fukata, 2006, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06).

Which Targets to Contact First to Maximize Influence over Social Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2013, SBP.

A New Method of Startup Planning for Boiling Water Reactors

Hiroshi Motoda, Takashi Kiguchi, Yasunori Bessho, 1981 .

Perspectives of Feature Selection

Hiroshi Motoda, Huan Liu, H. Motoda, 1998 .

A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree

Osamu Katai, Tetsuo Sawaragi, Takashi Washio, 1999, PAKDD.

Discovery of first-principle equations based on scale-type-based and data-driven reasoning

Takashi Washio, Hiroshi Motoda, 1998, Knowl. Based Syst..

Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002, PRICAI.

Opinion Formation by Voter Model with Temporal Decay Dynamics

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2012, ECML/PKDD.

Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2019, DS.

Guest Editors' Introduction: Feature Transformation and Subset Selection.

Hiroshi Motoda, Huan Liu, 1998 .

Looking back on the current day: interruptibility prediction using daily behavioral features

Jae-Gil Lee, Heeyoung Kim, Hiroshi Motoda, 2016, UbiComp.

A Plant Diagnosis Method Based on the Knowledge of System Description

Hiroshi Motoda, Naoyuki Yamada, H. Motoda, 1984 .

Characterization of Default Knowledge in Ripple Down Rules Method

Tadashi Horiuchi, Takashi Washio, Hiroshi Motoda, 1999, PAKDD.

Graph-based induction and its applications

Takashi Washio, Hiroshi Motoda, Takashi Matsuda, 2002, Adv. Eng. Informatics.

Discovery of Laws

Takashi Washio, Hiroshi Motoda, T. Washio, 2000 .

Case Generation Method for Constructing an RDR Knowledge Base and it’s Evaluation

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002 .

Active Mining: Second International Workshop, AM 2003, Maebashi, Japan, October 28, 2003, Revised Selected Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)

Shusaku Tsumoto, Masayuki Numao, Takahira Yamaguchi, 2005 .

Efficient analysis of node influence based on SIR model over huge complex networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2014, 2014 International Conference on Data Science and Advanced Analytics (DSAA).

Learning to Predict Opinion Share in Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010, AAAI.

A Knowledge based System for Plant Diagnosis

Hiroshi Motoda, Kenichi Yoshida, Naoyuki Yamada, 1984, Fifth Generation Computer Systems.

Feature Costruction for Classification Learning from Structured Data by Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002 .

"Teknowledge" Sells Knowledge Engineering(Conversation Room)

Hiroshi Motoda, Yasuhiro Kobayashi, H. Motoda, 1983 .

Expert Systems Research in Japan

Riichiro Mizoguchi, Hiroshi Motoda, 1995, IEEE Expert.

Rough Sets and Intelligent Systems Paradigms

Chris Cornelis, Hiroshi Motoda, Marzena Kryszkiewicz, 2014, Lecture Notes in Computer Science.

Constructing Decision Tree Based on Chunkingless Graph‐Based Induction

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2006 .

Performance Evaluation of Decision Tree Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2003, Discovery Science.

Super mediator - A new centrality measure of node importance for information diffusion over social network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2016, Inf. Sci..

Constructive Inductive Learning Based on Meta-attributes

Noboru Babaguchi, Hiroshi Motoda, Kouzou Ohara, 2004, Discovery Science.

Adaptive ripple down rules method based on minimum description length principle

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

Pattern Discovery from Graph-Structured Data - A Data Mining Perspective

Hiroshi Motoda, 2007, IEA/AIE.

Tables, Graphs and Logic for Induction

Hiroshi Motoda, Kenichi Yoshida, H. Motoda, 1995, Machine Intelligence 15.

Development of SDS2: Smart Discovery System for Simultaneous Equation Systems

Takashi Washio, Hiroshi Motoda, 1998, Discovery Science.

PRICAI’98: Topics in Artificial Intelligence

Hiroshi Motoda, Hing-Yan Lee, 1998, Lecture Notes in Computer Science.

Efficient Learning of User Conformity on Review Score

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2015, SBP.

Attribute Generation Based on Association Rules for Numerical Attribute Data

Takashi Washio, Hiroshi Motoda, Masahiro Terabe, 2001 .

Efficient Detection of Hot Span in Information Diffusion from Observation pdf

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2011, ArXiv.

Method to Make Apriori-based Graph Algorithm Efficiency

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 2001 .

Memory management of density-based spam detector

Katsuyuki Yamazaki, Takashi Washio, Hiroshi Motoda, 2005, The 2005 Symposium on Applications and the Internet.

PCLEARN: A model for learning perceptual-chunks

Masaki Suwa, Hiroshi Motoda, M. Suwa, 2019, Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society.

Consumer Behavior Analysis by Graph Mining Technique (post print version)

Katsutoshi Yada, Takashi Washio, Hiroshi Motoda, 2006 .

Data reduction: feature selection

Hiroshi Motoda, Huan Liu, H. Motoda, 2002 .

Speeding-up node influence computation for huge social networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2015, International Journal of Data Science and Analytics.

Development of startup control rod programming code system for BWRs

Hiroshi Motoda, Takashi Kiguchi, Yasunori Bessho, 1978 .

An Accurate and Efficient Method to Detect Critical Links to Maintain Information Flow in Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2017, ISMIS.

Compact Dual Ensembles for Active Learning

Huan Liu, Hiroshi Motoda, Amit Mandvikar, 2004, PAKDD.

Extracting influential nodes on a social network for information diffusion

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2009, Data Mining and Knowledge Discovery.

Consistency Based Feature Selection

Huan Liu, Hiroshi Motoda, Manoranjan Dash, 2000, PAKDD.

Detecting Critical Links in Complex Network to Maintain Information Flow/Reachability

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2016, PRICAI.

OPTIMAL ROD PROGRAMMING AND LOADING PATTERN IN A MULTIREGION REACTOR.

Hiroshi Motoda, Toshio Kawai, Takashi Kiguchi, 1972 .

Using a Hash-Based Method for Apriori-Based Graph Mining

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2004, PKDD.

Detecting Changes in Opinion Value Distribution for Voter Model

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2011, SBP.

Density-based spam detector

Katsuyuki Yamazaki, Takashi Washio, Hiroshi Motoda, 2004, IEICE Trans. Inf. Syst..

Workshop on Active Mining (AM-2004)

Shusaku Tsumoto, Masayuki Numao, Takahira Yamaguchi, 2004, JSAI Workshops.

Automated user modeling for intelligent interface

Hiroshi Motoda, Yoshida Kenichi, H. Motoda, 1995, Int. J. Hum. Comput. Interact..

Scientific Discovery of Dynamic Hidden States and Differential Law Equations (Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining) -- (Session 9: Scientific Data Mining)

Takashi Washio, Hiroshi Motoda, Fuminori Adachi, 2004 .

A Perceptual Criterion for Visually Controlling Learning

Masaki Suwa, Hiroshi Motoda, M. Suwa, 1993, ALT.

Operator Schemata Acquisition based on Recognition Propagation Rule

Masaki Suwa, Hiroshi Motoda, M. Suwa, 1995 .

Application of Qualitative Reasoning to Knowledge Acquisition

Hiroshi Motoda, Kenichi Yoshida, H. Motoda, 1991 .

Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002, Discovery Science.

Discovering Admissible Simultaneous Equations of Large Scale Systems

Takashi Washio, Hiroshi Motoda, T. Washio, 1998, AAAI/IAAI.

Selecting Information Diffusion Models over Social Networks for Behavioral Analysis

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010, ECML/PKDD.

Extracting Discriminative Patterns from Graph Structured Data Using Constrained Search

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2006, PKAW.

Complete Mining of Frequent Patterns from Graphs: Mining Graph Data

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 2003, Machine Learning.

Combining activity-evaluation information with NMF for trust-link prediction in social media

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2015, 2015 IEEE International Conference on Big Data (Big Data).

Introduction: special issue of selected papers of ACML 2012

Zhi-Hua Zhou, Steven C. H. Hoi, Hiroshi Motoda, 2013, Machine Learning.

Special feature on discovery science

Setsuo Arikawa, Hiroshi Motoda, 2009, New Generation Computing.

Fast Apriori-based Graph Mining Algorithm and application to 3-dimensional Structure Analysis

Takashi Washio, Hiroshi Motoda, Takashi Okada, 2003 .

Finding Relation between PageRank and Voter Model

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010, PKAW.

Learning to predict opinion share and detect anti-majority opinionists in social networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2013, Journal of Intelligent Information Systems.

Pruning Strategies Based on the Upper Bound of Information Gain for Discriminative Subgraph Mining

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2009, PKAW.

Optimization of Refueling Schedule for Light-Water Reactors

Hiroshi Motoda, Alexander Sesonske, John Herczeg, 1973 .

Advances in Knowledge Discovery and Data Mining

Jian Pei, Guandong Xu, Longbing Cao, 2014, Lecture Notes in Computer Science.

Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence: Topics in Artificial Intelligence

Hiroshi Motoda, Hing-Yan Lee, H. Motoda, 1998 .

Constructing a Decision Tree for Graph-Structured Data and its Applications

Hiroshi Motoda, Kouzou Ohara, Tetsuya Yoshida, 2004, Fundam. Informaticae.

Extracting Cooperative Structure among Online Items from Share-Event Sequence

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2018 .

Process Labeled Kernel Profiling: A New Facility to Profile System Activities

Hiroshi Motoda, Atsuo Kawaguchi, Shingo Nishioka, 1996, USENIX Annual Technical Conference.

Which is more influential, "Who" or "When" for a user to rate in online review site?

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2018, Intell. Data Anal..

Optimization of Fuel Assembly Allocation for Boiling Water Reactors

Hiroshi Motoda, Osamu Yokomizo, H. Motoda, 1976 .

Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002, PRICAI.

Efficient Estimation of Cumulative Influence for Multiple Activation Information Diffusion Model with Continuous Time Delay

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010, PRICAI.

Data Reduction via Instance Selection

Huan Liu, Hiroshi Motoda, H. Motoda, 2001 .

Computer Assisted Discovery of First Principle Equations from Numeric Data (Abstract)

Hiroshi Motoda, 1999, PAKDD.

Computational Methods of Feature Selection

Hiroshi Motoda, Huan Liu, D. Stracuzzi, 2022 .

Learning Information Diffusion Models from Observation and Its Application to Behavior Analysis

Hiroshi Motoda, 2011, SocInfo.

Part II of the Proceedings of the 9th International Conference on Advanced Data Mining and Applications - Volume 8347

Zhaohui Wu, Wei Wang, Longbing Cao, 2013 .

Discovering Time Differential Law Equations Containing Hidden State Variables and Chaotic Dynamics

Takashi Washio, Hiroshi Motoda, Fuminori Adachi, 2005, IJCAI.

Applying Data Mining to Field Quality Watchdog Task

Hirokazu Taki, Takashi Washio, Hiroshi Motoda, 2001 .

Automatic Web-Page Classification by Using Machine Learning Methods

Takashi Washio, Hiroshi Motoda, Makoto Tsukada, 2001, Web Intelligence.

Boiling water reactor control rod programming using heuristic and mathematical methods

Hiroshi Motoda, Tamotsu Hayase, 1980 .

Advances in Knowledge Discovery and Data Mining

Guandong Xu, Longbing Cao, Hiroshi Motoda, 2013, Lecture Notes in Computer Science.

On Issues of Instance Selection

Huan Liu, Hiroshi Motoda, H. Motoda, 2002, Data Mining and Knowledge Discovery.

Toward the Discovery of First Principle Based Scientific Law Equations

Takashi Washio, Hiroshi Motoda, T. Washio, 2002, Progress in Discovery Science.

Welcome from DSAA 2014 chairs

Philip S. Yu, Minyi Guo, Longbing Cao, 2014, DSAA.

Fast Method to Search Induced Sub-Graph from Massive Data

Takashi Washio, Hiroshi Motoda, Yoshio Nishimura, 2001 .

Search engine retrieval of changing information

Byeong Ho Kang, Hiroshi Motoda, Paul Compton, 2007, WWW '07.

Extension of Graph-Based Induction for General Graph Structured Data

Tadashi Horiuchi, Takashi Washio, Hiroshi Motoda, 2000, PAKDD.

Graph embedding on spheres and its application to visualization of information diffusion data

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2012, WWW.

Lecture Notes in Artificial Intelligence: Preface

Shusaku Tsumoto, Masayuki Numao, Takahira Yamaguchi, 2005 .

Consumer Behavior Analysis by Graph Mining Technique

Katsutoshi Yada, Takashi Washio, Hiroshi Motoda, 2006, KES.

Advances in Knowledge Discovery and Data Mining

Zhi-Hua Zhou, Ee-Peng Lim, Tru H. Cao, 2015, Lecture Notes in Computer Science.

Integrating Inductive Learning to the Ripple Down Rules Method with the Minimum Description Length Principle

Takashi Washio, Hiroshi Motoda, Takuya Wada, 2001 .

Basket Analysis on Meningitis Data

Takashi Washio, Hiroshi Motoda, Takayuki Ikeda, 2001, JSAI Workshops.

Proceedings of the Third International Workshop on Active Mining (AM-2004)

Shusaku Tsumoto, Masayuki Numao, Takahira Yamaguchi, 2004 .

Basket Analysis for Graph Structured Data

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 1999, PAKDD.

S3Bagging: Fast Classifier Induction Method with Subsampling and Bagging

Takashi Washio, Hiroshi Motoda, Masahiro Terabe, 2001, IDA.

Evaluation and Application

Hiroshi Motoda, Huan Liu, H. Motoda, 1998 .

State of the art of graph-based data mining

Takashi Washio, Hiroshi Motoda, T. Washio, 2003, SKDD.

A Framework of Numerical Basket Analysis

Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, 2005, 2005 Symposium on Applications and the Internet Workshops (SAINT 2005 Workshops).

SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos

Takashi Washio, Hiroshi Motoda, Fuminori Adachi, 2005, Discovery Science.

Preface

Tu Bao Ho, Hiroshi Motoda, Zhi-Hua Zhou, 1982, International Journal of Software and Informatics.

A Method to Divide Stream Data of Scores over Review Sites

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2014, PRICAI.

Interview-based knowledge acquisition using dynamic analysis

Riichiro Mizoguchi, Hiroshi Motoda, Atsuo Kawaguchi, 1991, IEEE Expert.

A General Framework for Mining Frequent Subgraphs from Labeled Graphs

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 2004, Fundam. Informaticae.

Advances in Knowledge Discovery and Data Mining

Guandong Xu, Longbing Cao, Hiroshi Motoda, 2013, Lecture Notes in Computer Science.

Data reduction: feature aggregation

Hiroshi Motoda, Huan Liu, H. Motoda, 2002 .

A Man-Machine Communication System for Boiling Water Reactor Core Management Planning

Hiroshi Motoda, Osamu Yokomizo, Takashi Kiguchi, 1976 .

Feature Selection with Selective Sampling

Huan Liu, Lei Yu, Hiroshi Motoda, 2002, International Conference on Machine Learning.

Learning Diffusion Probability Based on Node Attributes in Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2011, ISMIS.

Learning Attribute-weighted Voter Model over Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2011, ACML.

A Method for Generating a Control Rod Program for Boiling Water Reactors

Hiroshi Motoda, Takashi Kiguchi, Michihiro Ozawa, 1976 .

Efficient Estimation of Influence Functions for SIS Model on Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2009, IJCAI.

Analysis of Hepatitis Dataset by Decision Tree Based on Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2004, JSAI Workshops.

Scientific Discovery of Dynamic Models Based on Scale-type Constraints

Takashi Washio, Hiroshi Motoda, Fuminori Adachi, 2005 .

Rough Sets and Intelligent Systems Paradigms: Second International Conference, RSEISP 2014, Granada and Madrid, Spain, July 9-13, 2014

Chris Cornelis, Hiroshi Motoda, Davide Ciucci, 2014 .

Critical Link Identification Based on Bridge Detection for Network with Uncertain Connectivity

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2018, ISMIS.

Mining Association Rules for Estimation and Prediction

Takashi Washio, Hiroshi Motoda, T. Washio, 1998, PAKDD.

A Framework of Numerical Basket Analysis

Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, 2005 .

Discovery of Super-Mediators of Information Diffusion in Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010, Discovery Science.

Editorial: Data Mining Lessons Learned

Nada Lavrac, Hiroshi Motoda, Tom Fawcett, 2004, Machine Learning.

Enhancing the Plausibility of Law Equation Discovery

Takashi Washio, Hiroshi Motoda, Yuji Niwa, 2000, ICML.

Effective Visualization of Information Diffusion Process over Complex Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2008, ECML/PKDD.

Resampling-Based Framework for Estimating Node Centrality of Large Social Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2014, Discovery Science.

IEEE Intelligent Systems

Huan Liu, Hiroshi Motoda, S. Globali, 2019, Computer.

Graph-Based Induction for General Graph Structured Data and Its Application to Chemical Compound Data

Tadashi Horiuchi, Takashi Washio, Hiroshi Motoda, 2000, Discovery Science.

Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Kouzou Ohara, 2006, PAKDD.

Derivation of the Topology Structure from Massive Graph Data

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 1999, Discovery Science.

Extention of Basket Analysis and Quantitative Association Rule Mining(Graph Data Mining)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)

Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, 2004 .

Uncovering deception in social media

Jiawei Han, Huan Liu, Hiroshi Motoda, 2014, Social Network Analysis and Mining.

Adaptive Ripple Down Rules method based on minimum description length principle

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2004 .

Network Analysis of Three Twitter Functions: Favorite, Follow and Mention

Kazumi Saito, Hiroshi Motoda, Takayasu Fushimi, 2012, PKAW.

Feature Selection: An Ever Evolving Frontier in Data Mining

Huan Liu, Hiroshi Motoda, Rudy Setiono, 2010, FSDM.

On-line core performance prediction of BWR

Hiroshi Motoda, Takashi Kiguchi, Yasuo Nishizawa, 1975 .

Generative Models of Information Diffusion with Asynchronous Timedelay

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2010, ACML.

Automated user modeling for intelligent interface

Hiroshi Motoda, Kenichi Yoshida, H. Motoda, 1996, Int. J. Hum. Comput. Interact..

Active Mining Project: Overview

Shusaku Tsumoto, Masayuki Numao, Takahira Yamaguchi, 2003, Active Mining.

Communicability Criteria of Law Equations Discovery

Takashi Washio, Hiroshi Motoda, T. Washio, 2007, Computational Discovery of Scientific Knowledge.

Dynamic Scheduling for Web Monitoring Crawler

Byeong Ho Kang, Hiroshi Motoda, Paul Compton, 2009 .

Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains

Takashi Washio, Hiroshi Motoda, Yuji Niwa, 1999, IJCAI.

Effect of In/Out-Degree Correlation on Influence Degree of Two Contrasting Information Diffusion Models

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2012, SBP.

Feature Selection for Knowledge Discovery and Data Mining

Hiroshi Motoda, Huan Liu, H. Motoda, 1998, The Springer International Series in Engineering and Computer Science.

Critical Node Identification based on Articulation Point Detection for Uncertain Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2019, Int. J. Netw. Comput..

Proceedings of the 8th international conference on Discovery Science

Achim G. Hoffmann, Hiroshi Motoda, Tobias Scheffer, 2005 .

PCLEARN: A Computer Model for Learning Perceptual Chunks

Masaki Suwa, Hiroshi Motoda, M. Suwa, 1994, AI Commun..

International Workshop on Behavior Informatics (BI 2011): PC chairs' message

Longbing Cao, Jaideep Srivastava, Graham J. Williams, 2012, Pacific-Asia Conference on Knowledge Discovery and Data Mining.

Theory of Scale Types

Hiroshi Motoda, Takashi Washio, T. Washio, 1998 .

Unifying Learning Methods by Colored Digraphs

Hiroshi Motoda, Kenichi Yoshida, Nitin Indurkhya, 1993, ALT.

Minimizing the Spread of Contamination by Blocking Links in a Network

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2008, AAAI.

Resampling-based predictive simulation framework of stochastic diffusion model for identifying top-K influential nodes

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2013, International Journal of Data Science and Analytics.

Detecting changes in content and posting time distributions in social media

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

Deriving Class Association Rules Based on Levelwise Subspace Clustering

Takashi Washio, Hiroshi Motoda, Koutarou Nakanishi, 2005, PKDD.

Identifying Super-Mediators of Information Diffusion in Social Networks

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2013, Discovery Science.

An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data

Takashi Washio, Hiroshi Motoda, Akihiro Inokuchi, 2000, PKDD.

Solving the Contamination Minimization Problem on Networks for the Linear Threshold Model

Masahiro Kimura, Kazumi Saito, Hiroshi Motoda, 2008, PRICAI.

Experiments on Ripple Down Rules Method that Adapts to Changes in Class Distribution

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002 .

Knowledge discovery and data mining

Hongjun Lu, Hiroshi Motoda, Hing-Yan Lee, 1998, Knowl. Based Syst..

A Description Length-Based Decision Criterion for Default Knowledge in the Ripple Down Rules Method

Tadashi Horiuchi, Takashi Washio, Hiroshi Motoda, 2001, Knowledge and Information Systems.

The current status of expert system development and related technologies in Japan

Hiroshi Motoda, 1990, IEEE Expert.

Mining quantitative frequent itemsets using adaptive density-based subspace clustering

Takashi Washio, Hiroshi Motoda, Yuki Mitsunaga, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

Efficient analytical computation of expected frequency of motifs of small size by marginalization in uncertain network

Hiroshi Motoda, Takayasu Fushimi, Kazumi Saito, 2021, ASONAM.

General framework of opening and closing shops over a spatial network based on stochastic utility under competitive and time-bounded environment

Masahiro Kimura, Hiroshi Motoda, Takayasu Fushimi, 2021, Social Network Analysis and Mining.

Efficient computation of target-oriented link criticalness centrality in uncertain graphs

Masahiro Kimura, Hiroshi Motoda, Takayasu Fushimi, 2021, Intell. Data Anal..

A New Look at Default Knowledge in Ripple Down Rules Method

Tadashi Horiuchi, Takashi Washio, Hiroshi Motoda, 2000 .

Feature Selection Extraction and Construction

Hiroshi Motoda, Huan Liu, H. Motoda, 2002 .

A Theory of Control-Rod Programming Optimization in Two-Region Reactors

Hiroshi Motoda, Toshio Kawai, H. Motoda, 1970 .

Stochastic Fluctuation in a Uranium-Enriching Cascade Using the Centrifuge Process

Hiroshi Motoda, Toshio Kawai, Takashi Kiguchi, 1973 .

Applying Algebraic Mining Method of Graph Substructures to Mutageniesis Data Analysis

Takashi Washio, Hiroshi Motoda, Takashi Okada, 2008 .

Burnup Optimization of Continuous Scattered Refueling

Hiroshi Motoda, H. Motoda, 1970 .

Method for Evaluating the Local Variation of the Neutron Flux

Hiroshi Motoda, Yasuo Nishizawa, 1972 .

A Method for Calculating Power Distributions in Boiling Water Reactors Using In-Core Detector Readings

Hiroshi Motoda, Sadao Uchikawa, H. Motoda, 1981 .

Preliminary Analysis of Hepatitis Data by Beam-wise Graph-Based Induction

Takashi Washio, Hiroshi Motoda, Tetsuya Yoshida, 2002 .

On-Line Calculational Method for Evaluating the Power Distribution in a Nuclear Reactor Core

Hiroshi Motoda, Yasuo Nishizawa, H. Motoda, 1973 .

BURNUP OPTIMIZATION USING MODAL EXPANSION METHOD.

Masaharu Kitamura, Hiroshi Motoda, H. Motoda, 1972 .

Evaluation of on-line power-distribution prediction method by BWR operating data

Hiroshi Motoda, Takashi Kiguchi, Yasuo Nishizawa, 1977 .

OPTIMAL CONTROL ROD PROGRAMMING OF LIGHT WATER REACTORS IN EQUILIBRIUM FUEL CYCLE.

Hiroshi Motoda, H. Motoda, 1971 .

Applying the Apriori-based Graph Mining Method to Mutagenesis Data Analysis

Takashi Washio, Hiroshi Motoda, Takashi Okada, 2001 .

On-line prediction of the power distribution within boiling water reactors

Hiroshi Motoda, Takashi Kiguchi, Yasuo Nishizawa, 1976 .

Principles for control rod withdrawal strategy during the startup of boiling water reactors

Hiroshi Motoda, Yasunori Bessho, Mitsutaka Watanabe, 1982 .

Simple method to predict power level and core flow rate of boiling water reactors by using one-point core model.

Hiroshi Motoda, Kikuo Umegaki, Takashi Kiguchi, 1982 .

Feasibility Study of Core Management System by Data Communication for Boiling Water Reactors

Hiroshi Motoda, Takashi Kiguchi, H. Motoda, 1977 .

Investigation of the Fuel Loading Pattern on the Core Burnup by FLARE Simulation

Hiroshi Motoda, H. Motoda, 1972 .

Modeling Admissible Simultaneous Equation Systems Based on Complete Subsets and Scale-type Constraints

Takashi Washio, Hiroshi Motoda, .

Discovery of Possible LawFormulae Based on Measurement Scale

Takashi Washio, Hiroshi Motoda, 1996 .

Automated Scientific Modeling from Observed Data and its Application to Socio-Psychology

Takashi Washio, Hiroshi Motoda, Yuji Niwa, 2003 .

Development of a time-domain BWR core stability analysis program

Hiroshi Motoda, Osamu Yokomizo, I. Sumida, 1980 .

Optimization of Control Rod Programming and Loading Pattern in Multiregion Nuclear Reactor by the Method of Approximation Programming

Hiroshi Motoda, H. Motoda, 1972 .

Sensitivity Analysis of Ideal Centrifuge Cascade for Producing Slightly Enriched Uranium

Hiroshi Motoda, Toshio Kawai, Takashi Kiguchi, 1973 .

The Active Mining Project

Hiroshi Motoda, 2002 .

Extracting Behavioral Patterns from Relational History Data

Takashi Washio, Hiroshi Motoda, Toshihiro Kayama, 2007 .

Extension of Dimensional Analysis for Scale-types and its Application to Discovery of Admissible Models of Complex Processes

Takashi Washio, Hiroshi Motoda, 1999 .