International conference proceedings - Kudo Yasuo

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  1. A Vector Is a Granule: A Novel Extension of the Variable Precision Rough Set Model

    Hajime Okawa, Yasuo Kudo, and Tetsuya Murai，Proceedings of International Joint Conference on Rough Sets 2024，Springer，2024.05，Halifax

  2. Partial Discernibility Matrices for Enumerating Relative Reducts of Large Datasets

    Hajime Okawa, Yasuo Kudo, and Tetsuya Murai，Proc. of SCIS&ISIS2022，SOFT，2022.11，伊勢志摩

  3. Investigations of Interests that are Induced by Remarkers and their Remarks for Item Advertisements Based on Influencer's Recommendation

    Komei Arasawa, Shun Hattori, Yasuo Kudo，Proceedings of SCIS & ISIS 2018，(p.789 ～ 795)，IEEE CPS，2018.12，Toyama

  4. An Attempt of Object Reduction in Rough Set Theory

    Yasuo Kudo and Tetsuya Murai，Proceedings of SCIS & ISIS 2018，(p.33 ～ 36)，IEEE CPS，2018.12，Toyama

  5. Proposal of a Recommendation Method by Direct Setting of Preference Patterns Based on Interrelationship Mining

    Yasuo Kudo, Masashi Kuroda and Tetsuya Murai，Proceedings of ISASE-MAICS 2018，JSKE，2018.11，Spokane

  6. A Note on a Heuristic Attribute Reduction Method with Redundancy Checking

    Yasuo Kudo and Tetsuya Murai，Prof. of the 18th International Symposium on Advanced Intelligent Systems (ISIS2017)，(p.665 ～ 672)，KIIS，2017.10，Daegu

  7. Improvement of item-based collaborative filtering by adding time factor and covering degree

    Zhipeng Zhang, Yasuo Kudo, and Tetsuya Murai，Proc. of 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2016)，(p.543 ～ 547)，SOFT，2016.08，札幌市

  8. Modification of the covering-based collaborative filtering model to alleviate the new user cold-start problem

    Zhipeng Zhang, Yasuo Kudo, and Tetsuya Murai，Proc. of the 16th Int. Symposium on Advanced Intelligent Systems (ISIS 2015)，(p.1238 ～ 1249)，KIIS，2015.11，Mokpo

  9. On Representation Ability of Interrelated Attributes in Rough Set-based Interrelationship Mining

    Yasuo Kudo and Tetsuya Murai，Proc. of the 16th Int. Symposium on Advanced Intelligent Systems (ISIS 2015)，(p.1229 ～ 1237)，KIIS，2015.11，Mokpo

  10. Applying Covering-Based Rough Set Theory to User-Based Collaborative Filtering to Enhance the Quality of Recommendations

    Zhipeng Zhang, Yasuo Kudo, and Tetsuya Mura，Prof. of 4th Int. Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2015)，vol.LNAI 9376，(p.279 ～ 289)，Springer，2015.10，Nha Trang

  11. Some Properties of Interrelated Attributes in Relative Reducts for Interrelationship Mining

    Yasuo Kudo and Tetsuya Murai，Proceedings of Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2014)，(p.998 ～ 1001)，SOFT，2014.12，北九州

  12. Empty-Stringizing of the False Value in Crisp and Fuzzy Granular Hierarchical Structures

    Takehiro Tanaka , Tetsuya Murai , Yasuo Kudoy and Seiki Akama，Proceedings of Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2014)，(p.993 ～ 997)，SOFT，2014.12，北九州

  13. Da Costa Logics and Vagueness

    Seiki Akama, Tetsuya Murai, and Yasuo Kudo，2014 IEEE International Conference on Granular Computing (IEEE GrC2014)，(p.1 ～ 6)，IEEE，2014.10，登別

  14. Interrelationship Mining from a Viewpoint of Rough Sets on Two Universes

    Yasuo Kudo and Tetsuya Murai，2014 IEEE International Conference on Granular Computing (IEEE GrC2014)，(p.137 ～ 140)，IEEE，2014.10，登別

  15. Bi-superintuitionistic Logics for Rough Sets

    Seiki Akama, Tetsuya Murai, and Yasuo Kudo，2013 IEEE International Conference on Granular Computing (IEEE GrC2013)，(p.10 ～ 15)，IEEE，2013.12，Beijing

  16. Decision Logic for Rough Set-based Interrelationship Mining

    Yasuo Kudo and Tetsuya Murai，Proceeding of 2013 IEEE International Conference on Granular Computing (IEEE GrC2013)，(p.172 ～ 177)，IEEE，2013.12，Beijing

  17. Recommendation of a Cloud Service Item Based on Service Utilization Patterns in Jyaguchi

    Shree Krishna Shrestha, Yasuo Kudo, Bishnu Prasad Gautam, and Dipesh Shrestha，Knoledge and Systems Engineering，vol.AISC 245，(p.121 ～ 133)，Springer，2013.10，Hanoi

  18. On a Possibility of Applying Interrelationship Mining to Gene Expression Data Analysis

    Yasuo Kudo, Yoshifumi Okada, and Tetsuya Murai，Brain and Health Informatics，vol.LNAI 8211，(p.379 ～ 388)，Springer，2013.10，前橋

  19. Recommendation Method based on Rough Set for Sequential Data

    Daisuke Nagakubo, Yasuo Kudo, and Yoshifumi Okada，Proceedings of The International MultiConference of Engineers and Computer Science 2013 (IMECS2013)，(p.48 ～ 50)，IAENG，2013.03，Hong Kong

  20. Multidimensional Service Weight Sequence Mining based on Cloud Service Utilization in Jyaguchi

    Shree Krishna Shrestha, Yasuo Kudo, Bishnu Prasad Gautam, and Dipesh Shrestha，Proceedings of The International MultiConference of Engineers and Computer Science 2013 (IMECS2013)，(p.301 ～ 306)，IAENG，2013.03，Hong Kong

  21. A Parallel Computation Method of Attribute Reduction

    Yasuo Kudo and Tetsuya Murai，Proceedings of The 5th International Conference on Computational Intelligence and Industrial Applications (ISCIIA2012)，2012.08，札幌

  22. Indiscernibility Relations by Interrelationships between Attributes in Rough Set Data Analysis

    Yasuo Kudo and Tetsuya Murai，Proceeding of 2012 IEEE International Conference on Granular Computing (GrC2012)，(p.220 ～ 225)，IEEE，2012.08，HangZhou

  23. An Attempt of Reconstruction of Object-Oriented Rough Set Models

    Yasuo Kudo, Ken Kaneiwa, and Tetsuya Murai，Proceedings of 2011 IEEE International Conference on Granular Computing (IEEE GrC2011)，(p.345 ～ 350)，IEEE，2011.11，Kaohsiung

  24. A Heuristic Algorithm for Generating Decision Rules in Variable Precision Rough Set Models

    Yasuo Kudo and Tetsuya Murai，Proceedings of Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2010)，(p.1568 ～ 1573)，SOFT，2010.12，岡山

  25. Gene Expression Data Analysis Using Heuristic Attribute Reduction in Rough Set Theory

    Yasuo Kudo and Yoshifumi Okada，Proceedings of Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2010)，(p.1574 ～ 1578)，SOFT，2010.12，岡山

  26. An Attribute Reduction Algorithm by Switching Exhaustive and Heuristic Computation of Relative Reducts

    Yasuo Kudo and Tetsuya Murai，Proceedings of 2010 IEEE International Conference on Granular Computing (IEEE GrC2010)，(p.265 ～ 270)，IEEE，2010.08，San Jose

  27. Local Pattern Mining from Sequences using Rough Set Theory

    Ken Kaneiwa and Yasuo Kudo，Proceedings of 2010 IEEE International Conference on Granular Computing (IEEE GrC2010)，(p.247 ～ 252)，IEEE，2010.08，San Jose

  28. On a Criterion for Evaluating the Accuracy of Approximation by Variable Precision Rough Sets

    Yasuo Kudo and Tetsuya Murai，Integrated Uncertainty Management and Applications，vol.Advances in SoftComputing 68，(p.319 ～ 327)，Springer，2010.04，石川県能美市

  29. On a Criterion of Similarity between Partitions Based on Rough Set Theory

    Yasuo Kudo and Tetsuya Murai，Proceeding of 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC2009)，vol.LNAI5908，(p.101 ～ 108)，Springer，2009.12，New Delhi

  30. A Heuristic Algorithm for Attribute Reduction Based on Discernibility and Equivalence by Attributes

    Yasuo Kudo and Tetsuya Murai，Modeling Decisions for Artificial Intelligence (Proc. of MDAI2009)，(p.351 ～ 359)，Springer，2009.11，淡路

  31. On an Extraction Method of Structural Characteristics in Object-Oriented Rough Set Models

    Yasuo Kudo, Tetsuya Murai and Sadaaki Miyamoto，Proceeding of 2009 IEEE International Conference on Granular Computing (GrC2009)，(p.312 ～ 317)，IEEE，2009.08，Nanchang

  32. Attribute Reduction as Calculation of Focus in Granular Reasoning

    Yasuo Kudo and Tetsuya Murai，Proceedings of 39th International Symposium on Multiple-Valued Logic (ISMVL2009)，(p.274 ～ 279)，IEEE，2009.05，那覇

  33. A Heuristic Algorithm for Selective Calculation of a Better Relative Reduct in Rough Set Theory

    Yasuo Kudo and Tetsuya Murai，New Advances in Intelligent Decision Technologies，vol.SCI 199，(p.555 ～ 564)，Springer，2009.04，姫路

  34. Decision Matrices for Semi-Structured Decision Rules in Object-Oriented Rough Sets

    Yasuo Kudo and Tetsuya Murai，Proceeding of Soft Computing for Knowledge Technology Workshop (SCKT2008)，(p.27 ～ 36)，PRICAI，2008.12，Hanoi

  35. An Agent Control Method based on Rough-Set-based Granularity

    Seiki Ubukata, Yasuo Kudo and Tetsuya Murai，Proceedings of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2008)，(p.FR-G3-1 ～ )，SOFT，2008.09，名古屋

  36. A Modal Characterization of Granular Reasoning Based on Scott - Montague Models

    Yasuo Kudo and Tetsuya Murai，Proceedings of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2008)，(p.FR-G3-2 ～ )，SOFT，2008.09，名古屋

  37. An Application of Rough Set Analysis to a Psycho-physiological Study - Assessing the Relation between Psychological Scale and Immunological Biomarker

    Shusaku Nomura and Yasuo Kudo，Proceedings of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2008)，(p.TH-B3-2 ～ )，SOFT，2008.09，名古屋

  38. A Note on Characteristic Combination Patterns about How to Combine Objects in Object-Oriented Rough Set Models

    Yasuo Kudo and Tetsuya Murai，Proceeding of the Third International Conference on Rough Sets and Knowledge Technology (RSKT2008)，(p.115 ～ 123)，Springer，2008.06，Chengdu

  39. Rough Set Analysis on the Relation Between Human Psychological Mood State and the Immune Function

    Yasuo Kudo and Shusaku Nomura，Proceedings of 2008 IEEE Conference on Soft Computing in Industrial Applications，(p.228 ～ 233)，IEEE，2008.06，室蘭

  40. A Unified Formulation of Deduction, Induction and Abduction Using Granularity Based on Variable Precision Rough Set Models and Measure-Based Semantics for Modal Logics

    Yasuo Kudo, Tetusya Murai and Seiki Akama，Interval / Probabilistic Uncertainty and Non-classical Logics，vol.Advances in Soft Computing 46，(p.280 ～ 290)，Springer，2008.03，石川県能美市

  41. A Logical Representation of Images by Means of Multi-rough Sets for Kansei Image Retrieval

    Tetsuya Murai, Sadaaki Miyamoto and Yasuo Kudo，Rough Sets and Knowledge Technology，vol.LNAI 4481，(p.244 ～ 251)，Springer，2007.05，Toront

  42. Semi-Structured Decision Rules in Object-Oriented Rough Set Models for Kansei Engineering

    Yasuo Kudo and Tetsuya Murai，Rough Sets and Knowledge Technology，vol.LNAI 4481，(p.219 ～ 227)，Springer，2007.05，Toront

  43. Absent Value Semantics as IS-A Relationship in Object-Oriented Rough Set Models

    Yasuo Kudo and Tetsuya Murai，Proceeding of the International Symposium on Fuzzy and Rough Sets (ISFUROS2006)，2006.12，Santa Clara

  44. A Method of Generating Decision Rules in Object-Oriented Rough Set Models

    Yasuo Kudo and Tetsuya Murai，Rough Sets and Current Trends in Computing，vol.LNAI 4259，(p.338 ～ 347)，Springer，2006.11，神戸

  45. A Note on Treatment of Incomplete Information in Object-Oriented Rough Sets

    Yasuo Kudo and Tetsuya Murai，Proceedings of SCIS&ISIS 2006，(p.2238 ～ 2243)，SOFT，2006.09，Tokyo

  46. A Note on Granular Reasoning and Semantics of Four-Valued Logic

    Yasuo Kudo and Tetsuya Murai，Proceedings of the 7th International Conference on Computing Anticipatory Systems (CASYS'05)，(p.453 ～ 461)，AIP，2006.06，Liege

  47. New Logical Classes of Plausibility Functions in Dempster-Shafer Theory of Evidence

    Tetsuya Murai and Yasuo Kudo，Knowledge-Based Intelligent Information and Engineering Systems，vol.LNCS 3684，(4)，(p.675 ～ 681)，Springer，2005.09，Melbourne

  48. A Unified Framework of Propositional Knowledge Base Revision and Update Based on State Transition Models

    Yasuo Kudo and Tetsuya Murai，Proceeding of the 19th International Joint Conference on Artificial Intelligence (IJCAI'05)，(p.1568 ～ 1569)，IJCAI，2005.07，Edinburgh

  49. Paraconsistency and Paracompleteness in Chellas's Conditional Logics

    Tetsuya Murai, Yasuo Kudo, Seiki Akama and Jair M. Abe，Advances in Logic Based Intelligent Systems，(p.248 ～ 255)，IOS Press，2005，姫路

  50. Visibility and Focus: An Extended Framework for Granular Reasoning

    Yasuo Kudo and Tetsuya Murai，Advances in Logic Based Intelligent Systems，(p.280 ～ 287)，IOS Press，2005，姫路

  51. Monotonic and Nonmonotonic Reasoning in Zoom Reasoning Systems

    Tetsuya Murai, Masayuki Sanada, Yasuo Kudo, Yoshiharu Sato，Knowledge-Based Intelligent Information and Engineering Systems，vol.LNCS 3213，(p.1085 ～ 1091)，Springer，2004.09，Wellington

  52. A Method of Belief Base Revision for Extended Logic Programs Based on State Transition Diagrams

    Yasuo Kudo and Tetsuya Murai，Knowledge-Based Intelligent Information and Engineering Systems，vol.LNCS 3213，(1)，(p.1079 ～ 1084)，Springer，2004.09，Wellington

  53. A Note on Fuzzy Granular Reasoning

    Tetsuya Murai, Yasuo Kudo and Huynh Van Nam，Proccedings of 2004 IEEE International Conference of Fuzzy Systems (FUZZ-IEEE2004)，vol.1，(p.263 ～ 268)，IEEE，2004.07，Budapest

  54. Non-Monotonic Reasoning in Prioritized Knowledge Bases Based on Granular Reasoning

    Yasuo Kudo and Tetsuya Murai，Proccedings of 2004 IEEE International Conference of Fuzzy Systems (FUZZ-IEEE2004)，vol.1，(p.275 ～ 280)，IEEE，2004.07，Budapest

  55. Belief Base Revision of Horn Logic Programs Based on State Transition Diagrams

    Yasuo Kudo and Tetsuya Murai，Proceedings of the 8th World Multi-Conference on Systemics, Cybernetics and Infomatics (SCI2004)，vol.5，(p.69 ～ 74)，IIIS，2004.07，Orlando

  56. Fuzzy Reasoning in Zoom Reasoning Systems

    Tetsuya Murai and Yasuo Kudo，Proceedings of the 8th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI2004)，vol.5，(p.86 ～ 91)，IIIS，2004.07，Orlando

  57. A Note on Ziarko's Variable Precision Rough Set Model and Nonmonotonic Reasoning

    Tetsuya Murai, Masayuki Sanada, Yasuo Kudo, Mineichi Kudo，Rough Sets and Current Trends in Computing，vol.LNCS 3066，(p.103 ～ 108)，Springer，2004.06，Uppsala

  58. Association Rules and Dempster-Shafer Theory of Evidence

    Tetsuya Murai, Yasuo Kudo, Yoshiharu Sato，Discovery Science，vol.LNCS 2843，(p.377 ～ 384)，Springer，2003.10，札幌

  59. Rough and Fuzzy Sets from a Point of View of Propositional Annotated Modal Logic Part 1. Rough Fuzzy Sets

    Tetsuya Murai, Seiki Akama and Yasuo Kudo，Proceedings of the International Fuzzy Systems Association World Congress (IFSA2003)，2003.06，Istanbul

  60. A Note on Fuzzy Reasoning and Granularized Possible Worlds

    Tetsuya Murai, V. N. Huynh, Yasuo Kudo and M.Nakata，Proceedings of the Sixth International Conference on Computing Anticipatory Systems (CASYS'03)，AIP，2003，Liege

  61. Granular and Fuzzy Reasoning

    Tetsuya Murai, Yasuo Kudo, M.Nakata and Yoshiharu Sato，Proceedings of the International Symposium on Computational Intelligence and Intelligent Informatics 2003，(p.238 ～ 241)，SOFT，2003，Nabeul

  62. On the Development of a Virtual Dolphin Therapy System

    Yasuo Kudo, Keita Kojima and Takashi Uozumi，Proceedings of the International Symposium: Toward a Development of KANSEI Technology (KANSEI 2001)，(p.191 ～ 194)，2001，室蘭

  63. Knowledge Base Update and State Transitions in Possibility Theory

    Yasuo Kudo, Tetsuya Murai and Tsutomu Da-te，Proceedings of the International Conference on Artificial Intelligence (IC-AI'2000)，vol.1，(p.381 ～ 386)，CSREA Press，2000，Las Vegas

  64. Iterated Belief Update Based on Ordinal Conditional Functions

    Yasuo Kudo, Tetsuya Murai and Tsutomu Da-te，Proceedings of the Third International Conference on Knowledge-Based Intelligent Electronic Systems (KES'99)，vol.1，(p.526 ～ 529)，IEEE，1999，Aderade

  65. The Correspondence of Belief Changes in Logical Settings and the Possibilistic Framework

    Yasuo Kudo, Tetsuya Murai and Tsutomu Da-te，Proceedings of the Second International Conference on Knowledge-Based Intelligent Electronic Systems (KES'98)，(p.221 ～ 229)，IEEE，1998，Aderade

  66. A Possibilistic Interpretation of Extended Erasure

    Yasuo Kudo, Tetsuya Murai and Tsutomu Da-te，Proceedings of the Fifth European Congress of Intelligent Techniques and Soft Computing (EUFIT'97)，vol.1，(p.77 ～ 80)，Verlag Mainz，1997，Aachen

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