Michinori Nakata

Norio Saito

Takeshi Fujiwara

Proceedings of the Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, 2022

The Lattice Structure of Coverings in an Incomplete Information Table with Value Similarity.

[BibT_eX]

[DOI]

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2022

2021

Possible Coverings in Incomplete Information Tables with Similarity of Values.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2021

2020

NIS-Apriori-based rule generation with three-way decisions and its application system in SQL.

[BibT_eX]

[DOI]

Junzo Watada

Inf. Sci., 2020

An Adjusted Apriori Algorithm to Itemsets Defined by Tables and an Improved Rule Generator with Three-Way Decisions.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2020

2019

Guest Editorial: Rough Sets and Data Mining.

[BibT_eX]

[DOI]

CAAI Trans. Intell. Technol., 2019

Rough set-based rule generation and Apriori-based rule generation from table data sets: a survey and a combination.

[BibT_eX]

[DOI]

CAAI Trans. Intell. Technol., 2019

Rule induction based on rough sets from information tables having continuous domains.

[BibT_eX]

[DOI]

CAAI Trans. Intell. Technol., 2019

Rough Sets Based on Possible Indiscernibility Relations in Incomplete Information Tables with Continuous Values.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2019

NIS-Apriori Algorithm with a Target Descriptor for Handling Rules Supported by Minor Instances.

[BibT_eX]

[DOI]

Kao-Yi Shen

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2019

Rule Induction Based on Rough Sets from Possibilistic Data Tables.

[BibT_eX]

[DOI]

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2019

Rough Sets Based on Possibly Indiscernible Classes in Incomplete Information Tables with Continuous Values.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019, 2019

2018

On Two Apriori-Based Rule Generators: Apriori in Prolog and Apriori in SQL.

[BibT_eX]

[DOI]

Kao-Yi Shen

J. Adv. Comput. Intell. Intell. Informatics, 2018

Rule Induction Based on Indiscernible Classes from Rough Sets in Information Tables with Continuous Values.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2018

Rules Induced from Rough Sets in Information Tables with Continuous Values.

[BibT_eX]

[DOI]

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations, 2018

A Model of Rule Generation Handling Granules Defined by Implications in Table Data Sets.

[BibT_eX]

[DOI]

Junzo Watada

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

2017

A Proposal of Machine Learning by Rule Generation from Tables with Non-deterministic Information and Its Prototype System.

[BibT_eX]

[DOI]

Junzo Watada

Proceedings of the Rough Sets - International Joint Conference, 2017

Rough Sets in Incomplete Information Systems with Order Relations Under Lipski's Approach.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2017

2016

Rough Approximations from Indiscernibility Relations under Incomplete Information.

[BibT_eX]

[DOI]

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

On Apriori-Based Rule Generation in SQL - A Case of the Deterministic Information System.

[BibT_eX]

[DOI]

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

On NIS-Apriori Based Data Mining in SQL.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2016

Rough Sets by Indiscernibility Relations in Data Sets Containing Possibilistic Information.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2016

Describing Rough Approximations by Indiscernibility Relations in Information Tables with Incomplete Information.

[BibT_eX]

[DOI]

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

Information Dilution: Granule-Based Information Hiding in Table Data - A Case of Lenses Data Set in UCI Machine Learning Repository.

[BibT_eX]

[DOI]

Chenxi Liu

Proceedings of the Third International Conference on Computing Measurement Control and Sensor Network, 2016

A proposal of a privacy-preserving questionnaire by non-deterministic information and its analysis.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Granules for association rules and decision support in the getRNIA system.

[BibT_eX]

[DOI]

Intell. Decis. Technol., 2015

Families of the Granules for Association Rules and Their Properties.

[BibT_eX]

[DOI]

Chenxi Liu

Proceedings of the Rough Sets and Knowledge Technology - 10th International Conference, 2015

2014

Application of Rough Set-Based Information Analysis to Questionnaire Data.

[BibT_eX]

[DOI]

J. Adv. Comput. Intell. Intell. Informatics, 2014

Two Rough Set-based Software Tools for Analyzing Non-Deterministic Data.

[BibT_eX]

[DOI]

Int. J. Rough Sets Data Anal., 2014

Apriori-Based Rule Generation in Incomplete Information Databases and Non-Deterministic Information Systems.

[BibT_eX]

[DOI]

Fundam. Informaticae, 2014

An Approach Based on Rough Sets to Possibilistic Information.

[BibT_eX]

[DOI]

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2014

Reconsideration of rules in tables with non-deterministic data.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Granular Computing, 2014

Rule induction based on rough sets from possibilistic information under Lipski's approach.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Granular Computing, 2014

2013

Division Charts as Granules and Their Merging Algorithm for Rule Generation in Nondeterministic Data.

[BibT_eX]

[DOI]

Int. J. Intell. Syst., 2013

Twofold rough approximations under incomplete information.

[BibT_eX]

[DOI]

Int. J. Gen. Syst., 2013

Non-deterministic Information in Rough Sets: A Survey and Perspective.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Knowledge Technology - 8th International Conference, 2013

Rough Set-Based Information Dilution by Non-deterministic Information.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, 2013

An Overview of the getRNIA System for Non-deterministic Data.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference in Knowledge Based and Intelligent Information and Engineering Systems, 2013

Rule induction based on rough sets from information tables containing possibilistic information.

[BibT_eX]

[DOI]

Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting, 2013

2012

Association rule-based decision making in table data.

[BibT_eX]

[DOI]

Int. J. Reason. based Intell. Syst., 2012

Management of Information Incompleteness in Rough Non-deterministic Information Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances on Computational Intelligence, 2012

Division charts and their merging algorithm in Rough Non-deterministic information analysis.

[BibT_eX]

[DOI]

Proceedings of the 2012 IEEE International Conference on Granular Computing, 2012

Learning a Table from a Table with Non-deterministic Information: A Perspective.

[BibT_eX]

[DOI]

Proceedings of the Advanced Machine Learning Technologies and Applications, 2012

Rough Sets-Based Machine Learning over Non-deterministic Data: A Brief Survey.

[BibT_eX]

[DOI]

Proceedings of the Advanced Machine Learning Technologies and Applications, 2012

2011

Stable rule extraction and decision making in rough non-deterministic information analysis.

[BibT_eX]

[DOI]

Int. J. Hybrid Intell. Syst., 2011

A NIS-Apriori Based Rule Generator in Prolog and Its Functionality for Table Data.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Knowledge Technology - 6th International Conference, 2011

A Prototype System for Rule Generation in Lipski's Incomplete Information Databases.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, 2011

Dual Rough Approximations in Information Tables with Missing Values.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, 2011

Toward association rules based decision making in Lipski's Incomplete Information Databases.

[BibT_eX]

[DOI]

Proceedings of the 2011 IEEE International Conference on Granular Computing, 2011

Properties on inclusion relations and division charts in non-deterministic information systems.

[BibT_eX]

[DOI]

Proceedings of the 2011 IEEE International Conference on Granular Computing, 2011

2010

Rule Generation in Lipski's Incomplete Information Databases.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Current Trends in Computing, 2010

An overview of decision making in Rough Non-deterministic Information Analysis.

[BibT_eX]

[DOI]

Proceedings of the Second World Congress on Nature & Biologically Inspired Computing, 2010

Toward Rough Sets Based Rule Generation from Tables with Uncertain Numerical Values.

[BibT_eX]

[DOI]

Proceedings of the Integrated Uncertainty Management and Applications [revised papers from the International Symposium on Integrated Uncertainty Management and Applications, 2010

Two Rough Approximations for Information Tables Containing Missing Values.

[BibT_eX]

[DOI]

Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010

The Lower and the Upper Systems of Rules in Tables with Missing Values.

[BibT_eX]

[DOI]

Proceedings of the Database Theory and Application, Bio-Science and Bio-Technology, 2010

2009

Rough Sets under Non-deterministic Information.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Knowledge Technology, 4th International Conference, 2009

The Lower System, the Upper System and Rules with Stability Factor in Non-deterministic Information Systems.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, 2009

An Overview of a Software Tool in Rough Non-deterministic Information Analysis.

[BibT_eX]

[DOI]

Hiroshi Kimura

Proceedings of the ISMVL 2009, 2009

Applying Rough Sets to Information Tables Containing Missing Values.

[BibT_eX]

[DOI]

Proceedings of the ISMVL 2009, 2009

2008

Rules and Apriori Algorithm in Non-deterministic Information Systems.

[BibT_eX]

[DOI]

Trans. Rough Sets, 2008

Applying Rough Sets to Information Tables Containing Possibilistic Values.

[BibT_eX]

[DOI]

Trans. Comput. Sci., 2008

Rough Sets Based Rule Generation from Data with Categorical and Numerical Values.

[BibT_eX]

[DOI]

Kazuhiro Koba

J. Adv. Comput. Intell. Intell. Informatics, 2008

Lower and Upper Approximations of Rules in Non-deterministic Information Systems.

[BibT_eX]

[DOI]

Ryuji Ishibashi

Proceedings of the Rough Sets and Current Trends in Computing, 2008

Rough sets approximations in data tables containing missing values.

[BibT_eX]

[DOI]

Proceedings of the FUZZ-IEEE 2008, 2008

2007

Lower and Upper Approximations in Data Tables Containing Possibilistic Information.

[BibT_eX]

[DOI]

Trans. Rough Sets, 2007

On Possible Rules and Apriori Algorithm in Non-deterministic Information Systems: Part 2.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, 2007

Applying Rough Sets to Data Tables Containing Missing Values.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Intelligent Systems Paradigms, International Conference, 2007

On a Rough Sets Based Tool for Generating Rules from Data with Categorical and Numerical Values.

[BibT_eX]

[DOI]

Proceedings of the Modeling Decisions for Artificial Intelligence, 2007

Applying Rough Sets to Information Tables Containing Probabilistic Values.

[BibT_eX]

[DOI]

Proceedings of the Modeling Decisions for Artificial Intelligence, 2007

2006

An Application of Discernibility Functions to Generating Minimal Rules in Non-Deterministic Information Systems.

[BibT_eX]

[DOI]

J. Adv. Comput. Intell. Intell. Informatics, 2006

Generalizing Possibility-Based Fuzzy Relational Models.

[BibT_eX]

[DOI]

J. Adv. Comput. Intell. Intell. Informatics, 2006

Applying Rough Sets to Data Tables Containing Possibilistic Information.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Knowledge Technology, First International Conference, 2006

On Possible Rules and Apriori Algorithm in Non-deterministic Information Systems.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Current Trends in Computing, 2006

Applying Rough Sets to Data Tables Containing Imprecise Information Under Probabilistic Interpretation.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Current Trends in Computing, 2006

Rough Sets Approximations to Possibilistic Information.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Fuzzy Systems, 2006

2005

Discernibility Functions and Minimal Rules in Non-deterministic Information Systems.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, 2005

Rough Sets Handling Missing Values Probabilistically Interpreted.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, 2005

On a Tool for Rough Non-deterministic Information Analysis and Its Perspective for Handling Numerical Data.

[BibT_eX]

[DOI]

Proceedings of the Modeling Decisions for Artificial Intelligence, 2005

Checking Whether or Not Rough-Set-Based Methods to Incomplete Data Satisfy a Correctness Criterion.

[BibT_eX]

[DOI]

Proceedings of the Modeling Decisions for Artificial Intelligence, 2005

Rough Sets Based Minimal Certain Rule Generation in Non-deterministic Information Systems: An Overview.

[BibT_eX]

[DOI]

Proceedings of the Advances in Logic Based Intelligent Systems, 2005

Rough-set-based approaches to data containing incomplete information: possibility-based cases.

[BibT_eX]

[DOI]

Proceedings of the Advances in Logic Based Intelligent Systems, 2005

2004

Considering Semantic Ambiguity and Indistinguishability for Values of Membership Attribute in Possibility-Based Fuzzy Relational Models.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Current Trends in Computing, 2004

2003

Granular Reasoning Using Zooming In & Out: Aristotle's Categorical Syllogism.

[BibT_eX]

[DOI]

Proceedings of the International Workshop on Rough Sets in Knowledge Discovery and Soft Computing, 2003

Granular Reasoning Using Zooming In & Out.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, 2003

2002

Functional Dependencies in Relational Expressions Based on Or-Sets.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Current Trends in Computing, 2002

Association Rules and Non-Classical Logics.

[BibT_eX]

[DOI]

Proceedings of the 26th International Computer Software and Applications Conference (COMPSAC 2002), 2002

2001

A Note on Conditional Logic and Association Rules.

[BibT_eX]

[DOI]

Proceedings of the New Frontiers in Artificial Intelligence, 2001

A Note on Filtration and Granular Reasoning.

[BibT_eX]

[DOI]

Proceedings of the New Frontiers in Artificial Intelligence, 2001

Data Dependencies Over rough Relational Expressions.

[BibT_eX]

[DOI]

Proceedings of the 10th IEEE International Conference on Fuzzy Systems, 2001

2000

Handling Data with Plural Sources in Databases.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets and Current Trends in Computing, 2000

Semantic field: introduction.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, 2000

Semantic field as a bridge between data and decision.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, 2000

Generation of non-transitive chains from rational-valued and real-valued fuzzy subsets under rough set theory.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, 2000

1999

A Semantic-Ambiguity-Free Relational Model for Handling Imperfect Information<sup>1</sup>.

[BibT_eX]

[DOI]

J. Adv. Comput. Intell. Intell. Informatics, 1999

1998

On the treatment of imperfect information in intelligent databases.

[BibT_eX]

[DOI]

Proceedings of the Knowledge-Based Intelligent Electronic Systems, 1998

Generation of accessible worlds under available information.

[BibT_eX]

[DOI]

Masaru Shimbo

Proceedings of the Knowledge-Based Intelligent Electronic Systems, 1998

1997

Handling Imperfection in Databases: A Modal Logic Approach.

[BibT_eX]

[DOI]

Proceedings of the Database and Expert Systems Applications, 8th International Conference, 1997

1996

Unacceptable components in fuzzy relational databases.

[BibT_eX]

[DOI]