A Diagnosis Method of Dynamic System Using the Knowledge on System Description. - Naoyuki Yamada; Hiroshi Motoda (IJCAI, 1983)

A Knowledge based System for Plant Diagnosis. - Hiroshi Motoda; Naoyuki Yamada; Kenichi Yoshida (FGCS, 1984)

Proving Definite Clauses without Explicit Use of Inductions. - Akito Sakurai; Hiroshi Motoda (LP, 1988)

Acquisition of associative knowledge by the frustration-based learning method in an auxiliary-line problem. - Masaki Suwa; Hiroshi Motoda (Knowl. Acquis., 1989)

The Current Status of Expert System Development and Related Technologies in Japan. - Hiroshi Motoda (IEEE Expert, 1990)

The use of abstract primitives in representing the meanings of "Verbs" for understanding metaphors. - Masaki Suwa; Hiroshi Motoda (ALT, 1991)

Interview-Based Knowledge Acquisition Using Dynamic Analysis. - Atsuo Kawaguchi; Hiroshi Motoda; Riichiro Mizoguchi (IEEE Expert, 1991)

Knowledge Acquisition for Knowledge-Based Systems. - Hiroshi Motoda; Riichiro Mizoguchi; John H. Boose; Brian R. Gaines (IEEE Expert, 1991)

Learning Perceptually Chunked Macro Operators. - Masaki Suwa; Hiroshi Motoda (Machine Intelligence 13, 1992)

A New Algorithm for Automatic Configuration of Hidden Markov Models. - Makoto Iwayama; Nitin Indurkhya; Hiroshi Motoda (ALT, 1993)

A Perceptual Criterion for Visually Controlling Learning. - Masaki Suwa; Hiroshi Motoda (ALT, 1993)

Unifying Learning Methods by Colored Digraphs. - Kenichi Yoshida; Hiroshi Motoda; Nitin Indurkhya (ALT, 1993)

On dealing with dynamic utility of learned knowledge. - Masaki Suwa; Hiroshi Motoda (Machine Intelligence 14, 1993)

How Things Appear to Work: Predicting Behaviors from Device Diagrams. - N. Hari Narayanan; Masaki Suwa; Hiroshi Motoda (AAAI, 1994)

PCLEARN: A Computer Model for Learning Perceptual Chunks. - Masaki Suwa; Hiroshi Motoda (AI Commun., 1994)

Graph-based induction as a unified learning framework. - Kenichi Yoshida; Hiroshi Motoda; Nitin Indurkhya (Appl. Intell., 1994)

Tables, Graphs and Logic for Induction. - Kenichi Yoshida; Hiroshi Motoda (Machine Intelligence 15, 1995)

A Flash-Memory Based File System. - Atsuo Kawaguchi; Shingo Nishioka; Hiroshi Motoda (USENIX, 1995)

CLIP: Concept Learning from Inference Patterns. - Kenichi Yoshida; Hiroshi Motoda (Artif. Intell., 1995)

Expert Systems Research in Japan. - Riichiro Mizoguchi; Hiroshi Motoda (IEEE Expert, 1995)

A History-Oriented Envisioning Method. - Takashi Washio; Hiroshi Motoda (PRICAI, 1996)

Process Labeled Kernel Profiling: A New Facility to Profile System Activities. - Shingo Nishioka; Atsuo Kawaguchi; Hiroshi Motoda (USENIX ATC, 1996)

Automated user modeling for intelligent interface. - Kenichi Yoshida; Hiroshi Motoda (Int. J. Hum. Comput. Interact., 1996)

Discovering Admissible Models of Complex Systems Based on Scale-Types and Idemtity Constraints. - Takashi Washio; Hiroshi Motoda (IJCAI (2), 1997)

Help Desk System with Intelligent Interface. - Byeong Ho Kang 001; Kenichi Yoshida; Hiroshi Motoda; Paul Compton (Appl. Artif. Intell., 1997)

Feature Selection for Knowledge Discovery and Data Mining - Huan Liu 001; Hiroshi Motoda (Kluwer, 1998)

Discovering Admissible Simultaneous Equations of Large Scale Systems. - Takashi Washio; Hiroshi Motoda (AAAI/IAAI, 1998)

Development of SDS2: Smart Discovery System for Simultaneous Equation Systems. - Takashi Washio; Hiroshi Motoda (Discovery Science, 1998)

A Monotonic Measure for Optimal Feature Selection. - Huan Liu 001; Hiroshi Motoda; Manoranjan Dash (ECML, 1998)

Mining Association Rules for Estimation and Prediction. - Takashi Washio; Hiroshi Motoda (PAKDD, 1998)

Machine Learning Techniques to Make Computers Easier to Use. - Hiroshi Motoda; Kenichi Yoshida (Artif. Intell., 1998)

Guest Editors' Introduction: Feature Transformation and Subset Selection. - Huan Liu 001; Hiroshi Motoda (IEEE Intell. Syst., 1998)

Knowledge discovery and data mining. - Hing-Yan Lee; Hongjun Lu; Hiroshi Motoda (Knowl. Based Syst., 1998)

Discovery of first-principle equations based on scale-type-based and data-driven reasoning. - Takashi Washio; Hiroshi Motoda (Knowl. Based Syst., 1998)

Feature Selection Using Consistency Measure. - Manoranjan Dash; Huan Liu 001; Hiroshi Motoda (Discovery Science, 1999)

Derivation of the Topology Structure from Massive Graph Data. - Akihiro Inokuchi; Takashi Washio; Hiroshi Motoda (Discovery Science, 1999)

Graph-Based Induction for General Graph Structured Data. - Takashi Matsuda; Tadashi Horiuchi; Hiroshi Motoda; Takashi Washio; Kohei Kumazawa; Naohide Arai (Discovery Science, 1999)

Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains. - Takashi Washio; Hiroshi Motoda; Yuji Niwa (IJCAI, 1999)

Basket Analysis for Graph Structured Data. - Akihiro Inokuchi; Takashi Washio; Hiroshi Motoda; Kouhei Kumasawa; Naohide Arai (PAKDD, 1999)

Computer Assisted Discovery of First Principle Equations from Numeric Data (Abstract). - Hiroshi Motoda (PAKDD, 1999)

A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree. - Masahiro Terabe; Osamu Katai; Tetsuo Sawaragi; Takashi Washio; Hiroshi Motoda (PAKDD, 1999)

Characterization of Default Knowledge in Ripple Down Rules Method. - Takuya Wada; Tadashi Horiuchi; Hiroshi Motoda; Takashi Washio (PAKDD, 1999)

Graph-Based Induction for General Graph Structured Data and Its Application to Chemical Compound Data. - Takashi Matsuda; Tadashi Horiuchi; Hiroshi Motoda; Takashi Washio (Discovery Science, 2000)

Enhancing the Plausibility of Law Equation Discovery. - Takashi Washio; Hiroshi Motoda; Yuji Niwa (ICML, 2000)

Consistency Based Feature Selection. - Manoranjan Dash; Huan Liu 001; Hiroshi Motoda (PAKDD, 2000)

Extension of Graph-Based Induction for General Graph Structured Data. - Takashi Matsuda; Tadashi Horiuchi; Hiroshi Motoda; Takashi Washio (PAKDD, 2000)

An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data. - Akihiro Inokuchi; Takashi Washio; Hiroshi Motoda (PKDD, 2000)

Special Feature on Discovery Science. - Hiroshi Motoda; Setsuo Arikawa (New Gener. Comput., 2000)

Discovering Admissible Simultaneous Equation Models from Observed Data. - Takashi Washio; Hiroshi Motoda; Yuji Niwa (ECML, 2001)

S3Bagging: Fast Classifier Induction Method with Subsampling and Bagging. - Masahiro Terabe; Takashi Washio; Hiroshi Motoda (IDA, 2001)

Basket Analysis on Meningitis Data. - Takayuki Ikeda; Takashi Washio; Hiroshi Motoda (JSAI Workshops, 2001)

Knowledge Acquisition from Both Human Expert and Data. - Takuya Wada; Hiroshi Motoda; Takashi Washio (PAKDD, 2001)

Automatic Web-Page Classification by Using Machine Learning Methods. - Makoto Tsukada; Takashi Washio; Hiroshi Motoda (Web Intelligence, 2001)

A Description Length-Based Decision Criterion for Default Knowledge in the Ripple Down Rules Method. - Takuya Wada; Tadashi Horiuchi; Hiroshi Motoda; Takashi Washio (Knowl. Inf. Syst., 2001)

Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction. - Takashi Matsuda; Hiroshi Motoda; Tetsuya Yoshida; Takashi Washio (Discovery Science, 2002)

Toward the Discovery of First Principle Based Scientific Law Equations. - Takashi Washio; Hiroshi Motoda (Progress in Discovery Science, 2002)

Adaptive Ripple Down Rules Method based on Minimum Description Length Principle. - Tetsuya Yoshida; Hiroshi Motoda; Takashi Washio (ICDM, 2002)

Feature Selection with Selective Sampling. - Huan Liu 001; Hiroshi Motoda; Lei Yu 001 (ICML, 2002)

Case Generation Method for Constructing an RDR Knowledge Base. - Keisei Fujiwara; Tetsuya Yoshida; Hiroshi Motoda; Takashi Washio (PRICAI, 2002)

Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction. - Takashi Matsuda; Hiroshi Motoda; Tetsuya Yoshida; Takashi Washio (PRICAI, 2002)

Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data. - Takuya Wada; Tetsuya Yoshida; Hiroshi Motoda; Takashi Washio (PRICAI, 2002)

Graph-based induction and its applications. - Takashi Matsuda; Hiroshi Motoda; Takashi Washio (Adv. Eng. Informatics, 2002)

On Issues of Instance Selection. - Huan Liu 001; Hiroshi Motoda (Data Min. Knowl. Discov., 2002)

Attribute Generation Based on Association Rules. - Masahiro Terabe; Takashi Washio; Hiroshi Motoda; Osamu Katai; Tetsuo Sawaragi (Knowl. Inf. Syst., 2002)

Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction. - Warodom Geamsakul; Tetsuya Yoshida; Kouzou Ohara; Hiroshi Motoda; Takashi Washio; Hideto Yokoi; Katsuhiko Takabayashi (Active Mining, 2003)

Active Mining Project: Overview. - Shusaku Tsumoto; Takahira Yamaguchi; Masayuki Numao; Hiroshi Motoda (Active Mining, 2003)

Performance Evaluation of Decision Tree Graph-Based Induction. - Warodom Geamsakul; Takashi Matsuda; Tetsuya Yoshida; Hiroshi Motoda; Takashi Washio (Discovery Science, 2003)

Development of Generic Search Method Based on Transformation Invariance. - Fuminori Adachi; Takashi Washio; Hiroshi Motoda; Atsushi Fujimoto; Hidemitsu Hanafusa (ISMIS, 2003)

Classifier Construction by Graph-Based Induction for Graph-Structured Data. - Warodom Geamsakul; Takashi Matsuda; Tetsuya Yoshida; Hiroshi Motoda; Takashi Washio (PAKDD, 2003)

Active Feature Selection Using Classes. - Huan Liu 001; Lei Yu 001; Manoranjan Dash; Hiroshi Motoda (PAKDD, 2003)

Complete Mining of Frequent Patterns from Graphs: Mining Graph Data. - Akihiro Inokuchi; Takashi Washio; Hiroshi Motoda (Mach. Learn., 2003)

State of the art of graph-based data mining. - Takashi Washio; Hiroshi Motoda (SIGKDD Explor., 2003)

Preface. - Setsuo Arikawa; Koichi Furukawa; Shinichi Morishita; Hiroshi Motoda (Theor. Comput. Sci., 2003)

Constructive Inductive Learning Based on Meta-attributes. - Kouzou Ohara; Yukio Onishi; Noboru Babaguchi; Hiroshi Motoda (Discovery Science, 2004)

Analysis of Hepatitis Dataset by Decision Tree Based on Graph-Based Induction. - Warodom Geamsakul; Takashi Matsuda; Tetsuya Yoshida; Kouzou Ohara; Hiroshi Motoda; Takashi Washio; Hideto Yokoi; Katsuhiko Takabayashi (JSAI Workshops, 2004)

Workshop on Active Mining (AM-2004). - Masayuki Numao; Takahira Yamaguchi; Shusaku Tsumoto; Hiroshi Motoda (JSAI Workshops, 2004)

Consumer Behavior Analysis by Graph Mining Technique. - Katsutoshi Yada; Hiroshi Motoda; Takashi Washio; Asuka Miyawaki (KES, 2004)

Compact Dual Ensembles for Active Learning. - Amit Mandvikar; Huan Liu 001; Hiroshi Motoda (PAKDD, 2004)

Using a Hash-Based Method for Apriori-Based Graph Mining. - Phu Chien Nguyen; Takashi Washio; Kouzou Ohara; Hiroshi Motoda (PKDD, 2004)

A selective sampling approach to active feature selection. - Huan Liu 001; Hiroshi Motoda; Lei Yu 001 (Artif. Intell., 2004)

Adaptive Ripple Down Rules method based on minimum description length principle. - Tetsuya Yoshida; Takuya Wada; Hiroshi Motoda; Takashi Washio (Intell. Data Anal., 2004)

Density-Based Spam Detector. - Kenichi Yoshida; Fuminori Adachi; Takashi Washio; Hiroshi Motoda; Teruaki Homma; Akihiro Nakashima; Hiromitsu Fujikawa; Katsuyuki Yamazaki (IEICE Trans. Inf. Syst., 2004)

Editorial: Data Mining Lessons Learned. - Nada Lavrac; Hiroshi Motoda; Tom Fawcett (Mach. Learn., 2004)

Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. - Nada Lavrac; Hiroshi Motoda; Tom Fawcett; Robert Holte; Pat Langley; Pieter W. Adriaans (Mach. Learn., 2004)

Performance evaluation of fusing two different knowledge sources in Ripple Down Rules method. - Tetsuya Yoshida; Hiroshi Motoda (AMT, 2005)

Refining diagnostic knowledge extracted from interferon therapy by graph-based induction. - Tetsuya Yoshida; Akira Mogi; Kouzou Ohara; Hiroshi Motoda; Takashi Washio (AMT, 2005)

Graph Clustering Based on Structural Similarity of Fragments. - Tetsuya Yoshida; Ryosuke Shoda; Hiroshi Motoda (Federation over the Web, 2005)

SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos. - Takashi Washio; Fuminori Adachi; Hiroshi Motoda (Discovery Science, 2005)

Efficient Mining of High Branching Factor Attribute Trees. - Alexandre Termier; Marie-Christine Rousset; Michèle Sebag; Kouzou Ohara; Takashi Washio; Hiroshi Motoda (ICDM, 2005)

Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering. - Takashi Washio; Yuki Mitsunaga; Hiroshi Motoda (ICDM, 2005)

Discovering Time Differential Law Equations Containing Hidden State Variables and Chaotic Dynamics. - Takashi Washio; Fuminori Adachi; Hiroshi Motoda (IJCAI, 2005)

Mutagenicity Risk Analysis by Using Class Association Rules. - Takashi Washio; Koutarou Nakanishi; Hiroshi Motoda; Takashi Okada (JSAI Workshops, 2005)

Cl-GBI: A Novel Approach for Extracting Typical Patterns from Graph-Structured Data. - Phu Chien Nguyen; Kouzou Ohara; Hiroshi Motoda; Takashi Washio (PAKDD, 2005)

Deriving Class Association Rules Based on Levelwise Subspace Clustering. - Takashi Washio; Koutarou Nakanishi; Hiroshi Motoda (PKDD, 2005)

A Framework of Numerical Basket Analysis. - Takashi Washio; Atsushi Fujimoto; Hiroshi Motoda (SAINT Workshops, 2005)

Memory Management of Density-Based Spam Detector. - Kenichi Yoshida; Fuminori Adachi; Takashi Washio; Hiroshi Motoda; Teruaki Homma; Akihiro Nakashima; Hiromitsu Fujikawa; Katsuyuki Yamazaki (SAINT, 2005)

Constructing a Decision Tree for Graph-Structured Data and its Applications. - Warodom Geamsakul; Tetsuya Yoshida; Kouzou Ohara; Hiroshi Motoda; Hideto Yokoi; Katsuhiko Takabayashi (Fundam. Informaticae, 2005)

A General Framework for Mining Frequent Subgraphs from Labeled Graphs. - Akihiro Inokuchi; Takashi Washio; Hiroshi Motoda (Fundam. Informaticae, 2005)

Enhancing the plausibility of law equation discovery through cross check among multiple scale-type-based models. - Takashi Washio; Hiroshi Motoda; Yuji Niwa (J. Exp. Theor. Artif. Intell., 2005)

Multi-structure Information Retrieval Method Based on Transformation Invariance. - Fuminori Adachi; Takashi Washio; Atsushi Fujimoto; Hiroshi Motoda; Hidemitsu Hanafusa (New Gener. Comput., 2005)

What Can We Do with Graph-Structured Data? - A Data Mining Perspective. - Hiroshi Motoda (Australian Conference on Artificial Intelligence, 2006)

A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis. - Kenta Fukata; Takashi Washio; Hiroshi Motoda (ICDM Workshops, 2006)

Analysis on a Relation Between Enterprise Profit and Financial State by Using Data Mining Techniques. - Takashi Washio; Yasuo Shinnou; Katsutoshi Yada; Hiroshi Motoda; Takashi Okada (JSAI, 2006)

Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction. - Phu Chien Nguyen; Kouzou Ohara; Akira Mogi; Hiroshi Motoda; Takashi Washio (PAKDD, 2006)

Extracting Discriminative Patterns from Graph Structured Data Using Constrained Search. - Kiyoto Takabayashi; Phu Chien Nguyen; Kouzou Ohara; Hiroshi Motoda; Takashi Washio (PKAW, 2006)

A study on rough set-aided feature selection for automatic web-page classification. - Toshiko Wakaki; Hiroyuki Itakura; Masaki Tamura; Hiroshi Motoda; Takashi Washio (Web Intell. Agent Syst., 2006)

Communicability Criteria of Law Equations Discovery. - Takashi Washio; Hiroshi Motoda (Computational Discovery of Scientific Knowledge, 2007)

Pattern Discovery from Graph-Structured Data - A Data Mining Perspective. - Hiroshi Motoda (IEA/AIE, 2007)

Search engine retrieval of changing information. - Yang Sok Kim; Byeong Ho Kang 001; Paul Compton; Hiroshi Motoda (WWW, 2007)

Scientific Discovery of Dynamic Models Based on Scale-type Constraints. - Fuminori Adachi; Takashi Washio; Hiroshi Motoda (Inf. Media Technol., 2007)

A Classification Method Based on Subspace Clustering and Association Rules. - Takashi Washio; Koutarou Nakanishi; Hiroshi Motoda (New Gener. Comput., 2007)

Minimizing the Spread of Contamination by Blocking Links in a Network. - Masahiro Kimura; Kazumi Saito; Hiroshi Motoda (AAAI, 2008)

Community analysis of influential nodes for information diffusion on a social network. - Masahiro Kimura; Kazumasa Yamakawa; Kazumi Saito; Hiroshi Motoda (IJCNN, 2008)

What Does an Information Diffusion Model Tell about Social Network Structure?. - Takayasu Fushimi; Takashi Kawazoe; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (PKAW, 2008)

Pruning Strategies Based on the Upper Bound of Information Gain for Discriminative Subgraph Mining. - Kouzou Ohara; Masahiro Hara; Kiyoto Takabayashi; Hiroshi Motoda; Takashi Washio (PKAW, 2008)

Effective Visualization of Information Diffusion Process over Complex Networks. - Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (ECML/PKDD (2), 2008)

Solving the Contamination Minimization Problem on Networks for the Linear Threshold Model. - Masahiro Kimura; Kazumi Saito; Hiroshi Motoda (PRICAI, 2008)

Top 10 algorithms in data mining. - Xindong Wu 001; Vipin Kumar 001; J. Ross Quinlan; Joydeep Ghosh; Qiang Yang 001; Hiroshi Motoda; Geoffrey J. McLachlan; Angus F. M. Ng; Bing Liu 001; Philip S. Yu; Zhi-Hua Zhou; Michael S. Steinbach; et al. (Knowl. Inf. Syst., 2008)

DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm. - Alexandre Termier; Marie-Christine Rousset; Michèle Sebag; Kouzou Ohara; Takashi Washio; Hiroshi Motoda (IEEE Trans. Knowl. Data Eng., 2008)

Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (ACML, 2009)

Discovering Influential Nodes for SIS Models in Social Networks. - Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (Discovery Science, 2009)

Efficient Estimation of Influence Functions for SIS Model on Social Networks. - Masahiro Kimura; Kazumi Saito; Hiroshi Motoda (IJCAI, 2009)

Preface. - Tu Bao Ho; Zhi-Hua Zhou; Hiroshi Motoda (Int. J. Softw. Informatics, 2009)

Blocking links to minimize contamination spread in a social network. - Masahiro Kimura; Kazumi Saito; Hiroshi Motoda (ACM Trans. Knowl. Discov. Data, 2009)

Learning to Predict Opinion Share in Social Networks. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (AAAI, 2010)

Discovery of Super-Mediators of Information Diffusion in Social Networks. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (Discovery Science, 2010)

Finding Relation between PageRank and Voter Model. - Takayasu Fushimi; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda; Kouzou Ohara (PKAW, 2010)

Acquiring Expected Influence Curve from Single Diffusion Sequence. - Yuya Yoshikawa; Kazumi Saito; Hiroshi Motoda; Kouzou Ohara; Masahiro Kimura (PKAW, 2010)

Selecting Information Diffusion Models over Social Networks for Behavioral Analysis. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (ECML/PKDD (3), 2010)

Efficient Estimation of Cumulative Influence for Multiple Activation Information Diffusion Model with Continuous Time Delay. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (PRICAI, 2010)

Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (SBP, 2010)

Extracting influential nodes on a social network for information diffusion. - Masahiro Kimura; Kazumi Saito; Ryohei Nakano; Hiroshi Motoda (Data Min. Knowl. Discov., 2010)

Editorial. - Tu Bao Ho; Zhi-Hua Zhou; Hiroshi Motoda (Intell. Data Anal., 2010)

Preface. - Huan Liu 001; Hiroshi Motoda; Rudy Setiono; Zheng Zhao 002 (FSDM, 2010)

Feature Selection: An Ever Evolving Frontier in Data Mining. - Huan Liu 001; Hiroshi Motoda; Rudy Setiono; Zheng Zhao 002 (FSDM, 2010)

Generative Models of Information Diffusion with Asynchronous Timedelay. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (ACML, 2010)

Speeding Up Bipartite Graph Visualization Method. - Takayasu Fushimi; Yamato Kubota; Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (Australasian Conference on Artificial Intelligence, 2011)

Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (Discovery Science, 2011)

Learning Diffusion Probability Based on Node Attributes in Social Networks. - Kazumi Saito; Kouzou Ohara; Yuki Yamagishi; Masahiro Kimura; Hiroshi Motoda (ISMIS, 2011)

Detecting Changes in Opinion Value Distribution for Voter Model. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (SBP, 2011)

Learning Information Diffusion Models from Observation and Its Application to Behavior Analysis. - Hiroshi Motoda (SocInfo, 2011)

Efficient Detection of Hot Span in Information Diffusion from Observation - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (CoRR, 2011)

Learning information diffusion model in a social network for predicting influence of nodes. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (Intell. Data Anal., 2011)

Estimating Diffusion Probability Changes for AsIC-SIS Model. - Akihiro Koide; Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (ACML, 2011)

Learning Attribute-weighted Voter Model over Social Networks. - Yuki Yamagishi; Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (ACML, 2011)

Burst Detection in a Sequence of Tweets Based on Information Diffusion Model. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (Discovery Science, 2012)

Network Analysis of Three Twitter Functions: Favorite, Follow and Mention. - Shoko Kato; Akihiro Koide; Takayasu Fushimi; Kazumi Saito; Hiroshi Motoda (PKAW, 2012)

Opinion Formation by Voter Model with Temporal Decay Dynamics. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (ECML/PKDD (2), 2012)

Effect of In/Out-Degree Correlation on Influence Degree of Two Contrasting Information Diffusion Models. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (SBP, 2012)

Graph embedding on spheres and its application to visualization of information diffusion data. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (WWW (Companion Volume), 2012)

Learning Asynchronous-Time Information Diffusion Models and its Application to Behavioral Data Analysis over Social Networks - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (CoRR, 2012)

Efficient discovery of influential nodes for SIS models in social networks. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (Knowl. Inf. Syst., 2012)

Predictive Simulation Framework of Stochastic Diffusion Model for Identifying Top-K Influential Nodes. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (ACML, 2013)

Detecting changes in content and posting time distributions in social media. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (ASONAM, 2013)

Identifying Super-Mediators of Information Diffusion in Social Networks. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (Discovery Science, 2013)

Which Targets to Contact First to Maximize Influence over Social Network. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (SBP, 2013)

Learning to predict opinion share and detect anti-majority opinionists in social networks. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (J. Intell. Inf. Syst., 2013)

Special issue on behavior computing. - Longbing Cao; Philip S. Yu; Hiroshi Motoda; Graham J. Williams (Knowl. Inf. Syst., 2013)

Introduction: special issue of selected papers of ACML 2012. - Zhi-Hua Zhou; Wee Sun Lee; Steven C. H. Hoi; Wray L. Buntine; Hiroshi Motoda (Mach. Learn., 2013)

Detecting changes in information diffusion patterns over social networks. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (ACM Trans. Intell. Syst. Technol., 2013)

Resampling-Based Framework for Estimating Node Centrality of Large Social Network. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (Discovery Science, 2014)

Efficient analysis of node influence based on SIR model over huge complex networks. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (DSAA, 2014)

Welcome from DSAA 2014 chairs. - Philip S. Yu; Masaru Kitsuregawa; Hiroshi Motoda; Bart Goethals; Minyi Guo; Longbing Cao; George Karypis; Irwin King; Wei Wang 379 (DSAA, 2014)

Analyzing Mediator-Activity Effects for Trust-Network Evolution in Social Media. - Keito Hatta; Masahito Kumano; Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (PRICAI, 2014)

A Method to Divide Stream Data of Scores over Review Sites. - Yuki Yamagishi; Seiya Okubo; Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (PRICAI, 2014)

A New Approach for Item Ranking Based on Review Scores Reflecting Temporal Trust Factor. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (SBP, 2014)

Uncovering deception in social media. - Huan Liu 001; Jiawei Han 001; Hiroshi Motoda (Soc. Netw. Anal. Min., 2014)

Combining activity-evaluation information with NMF for trust-link prediction in social media. - Kanji Matsutani; Masahito Kumano; Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (IEEE BigData, 2015)

Change Point Detection for Information Diffusion Tree. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (Discovery Science, 2015)

Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (PAKDD (1), 2015)

Efficient Learning of User Conformity on Review Score. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (SBP, 2015)

Change point detection for burst analysis from an observed information diffusion sequence of tweets. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (J. Intell. Inf. Syst., 2015)

Accelerating Computation of Distance Based Centrality Measures for Spatial Networks. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (DS, 2016)

Looking back on the current day: interruptibility prediction using daily behavioral features. - Minsoo Choy; Daehoon Kim; Jae-Gil Lee 001; Heeyoung Kim; Hiroshi Motoda (UbiComp, 2016)

Detecting Critical Links in Complex Network to Maintain Information Flow/Reachability. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (PRICAI, 2016)

Speeding-up node influence computation for huge social networks. - Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (Int. J. Data Sci. Anal., 2016)

Super mediator - A new centrality measure of node importance for information diffusion over social network. - Kazumi Saito; Masahiro Kimura; Kouzou Ohara; Hiroshi Motoda (Inf. Sci., 2016)

Maximizing Network Performance Based on Group Centrality by Creating Most Effective k-Links. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (DSAA, 2017)

Discovering Cooperative Structure Among Online Items for Attention Dynamics. - Kanji Matsutani; Masahito Kumano; Masahiro Kimura; Kazumi Saito; Kouzou Ohara; Hiroshi Motoda (ICDM Workshops, 2017)

An Accurate and Efficient Method to Detect Critical Links to Maintain Information Flow in Network. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (ISMIS, 2017)

Critical Node Identification Based on Articulation Point Detection for Network with Uncertain Connectivity. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (CANDAR, 2018)

Critical Link Identification Based on Bridge Detection for Network with Uncertain Connectivity. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (ISMIS, 2018)

Efficient Detection of Critical Links to Maintain Performance of Network with Uncertain Connectivity. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (PRICAI (1), 2018)

Which is more influential, "Who" or "When" for a user to rate in online review site? - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (Intell. Data Anal., 2018)

Accurate and efficient detection of critical links in network to minimize information loss. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (J. Intell. Inf. Syst., 2018)

Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (DS, 2019)

Efficient Identification of Critical Links Based on Reachability Under the Presence of Time Constraint. - Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (PRICAI (2), 2019)

Critical Node Identification based on Articulation Point Detection for Uncertain Network. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (Int. J. Netw. Comput., 2019)

Opening and Closing Dynamics of Competing Shop Groups over Spatial Networks. - Takayasu Fushimi; Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (ASONAM, 2020)

Efficient Computing of PageRank Scores on Exact Expected Transition Matrix of Large Uncertain Graph. - Takayasu Fushimi; Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (IEEE BigData, 2020)

Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links. - Kouzou Ohara; Takayasu Fushimi; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (DS, 2020)

Resampling-based predictive simulation framework of stochastic diffusion model for identifying top-K influential nodes. - Kouzou Ohara; Kazumi Saito; Masahiro Kimura; Hiroshi Motoda (Int. J. Data Sci. Anal., 2020)

Efficient analytical computation of expected frequency of motifs of small size by marginalization in uncertain network. - Takayasu Fushimi; Kazumi Saito; Hiroshi Motoda (ASONAM, 2021)

Efficient computation of target-oriented link criticalness centrality in uncertain graphs. - Kazumi Saito; Takayasu Fushimi; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (Intell. Data Anal., 2021)

General framework of opening and closing shops over a spatial network based on stochastic utility under competitive and time-bounded environment. - Takayasu Fushimi; Kazumi Saito; Kouzou Ohara; Masahiro Kimura; Hiroshi Motoda (Soc. Netw. Anal. Min., 2021)

Efficient computation of expected motif frequency in uncertain graphs by exploiting possible world marginalization and motif transition. - Takayasu Fushimi; Kazumi Saito; Hiroshi Motoda (Soc. Netw. Anal. Min., 2022)

Constructing outlier-free histograms with variable bin-width based on distance minimization. - Takayasu Fushimi; Kazumi Saito; Hiroshi Motoda (Intell. Data Anal., 2023)