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A Knowledge Revision Method based on Similarity Observations

Research Project

Project/Area Number 11680375
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionHokkaido University

Principal Investigator

HARAGUCHI Makoto  Hokkaido University Graduate School of Engineering, Professor, 大学院・工学研究科, 教授 (40128450)

Co-Investigator(Kenkyū-buntansha) KAKUTA Tokuyasu  Graduate School of Law, Lecturer, 大学院・法学研究科, 講師 (80292001)
SADOHARA Ken  Electrotechnical Laboratory, Researcher, 知能情報部, 研究員
OKUBO Yoshiaki  Hokkaido University, Graduate School of Engineering, Instructor, 大学院・工学研究科, 助手 (40271639)
Project Period (FY) 1999 – 2000
Project Status Completed (Fiscal Year 2000)
Budget Amount *help
¥2,800,000 (Direct Cost: ¥2,800,000)
Fiscal Year 2000: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1999: ¥1,300,000 (Direct Cost: ¥1,300,000)
KeywordsKnowledge revision / Similarity between concept / Abstraction-based similarity detection / 知識の更新 / ゴールに依存した類似性 / 型の特殊化
Research Abstract

We proposes a new framework of knowledge revision, called Similarity-Driven Knowledge Revision.
In our framework, the revision is invoked based on a similarity observation by users and is intended to match with the observation.
Particularly, we are concerned with a revision strategy according to which an inadequate typing in describing an object-oriented knowledge base is corrected and revised by specializing the inadequate types to more specific ones without loss of original inference power.
That is, a minimal revision can be achieved according to our revision framework.
In order to realize it, we introduce a notion of{\em extended sorts}.
An extended sort can be viewed as a concept that does not appear explicitly in the original knowledge base.
If a variable typing with some sort is considered too general in the original knowledge base, the typing is modified by replacing the general sort with more specific extended sort.
Such an extended sort can be identified by forward reasoning from the original knowledge base.
Especially, a forward reasoning with SOL-deduction is adopted to obtain extended sorts efficiently.
Some experimental results show that the use of SOL-deduction can drastically improve the computational efficiency.

Report

(3 results)
  • 2000 Annual Research Report   Final Research Report Summary
  • 1999 Annual Research Report
  • Research Products

    (22 results)

All Other

All Publications (22 results)

  • [Publications] Y.Itoh and M.Haraguchi: "Conceptual Classifications Guided by a Concept Hierarchy"Lecture Notes in Artificial Intelligence. vol.1968. 166-178 (2000)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] M.Haraguchi: "Analogical Classification based on Abstraction"Proc.17^<th> Workshop on Machine Intelligence. 29-31 (2000)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] 工藤嘉晃,原口誠: "適切な抽象化に基づくデータベースの一般化によるデータマイニング"人工知能学会誌. vol.15,No.4. 638-648 (2000)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] T.Kakuta,M.Haraguchi: "A demonstration of a legal reasoning system based on teleological analogies"Pro.of the 7^<th> International Conference on Artificial Intelligence and Law. 196-205 (1999)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] N.Morita,M.Haraguchi,Y.Okubo: "A Method of Similarity-Driven Knowledge Revision for Type Specializations"Lecture Notes in Artificial Intelligence. vol.1720. 194-205 (1999)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] Y.Kudoh,M.Haraguchi: "An appropirate Abstraction for an Attribute-Oriented Induction"Lecture Notes in Artificial Intelligence. vol.1721. 43-55 (1999)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] 原口誠,角田篤泰: "法律人工知能(吉野一編)「法の目的に適った法的類推の実現」(pp.358〜369分担)"創成社. 394 (2000)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] Y.Itoh and M.Haraguchi: "Conceptual Classifications Guided by a Concept Hierarchy"Lecture Notes in Artificial Intelligence. Vol.1968. 166-178 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] M.Haraguchi: "Analogical Classification based on Abstraction"Proc.17th Workshop on Machine Intelligence. 29-31 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] T.Kakuta, M.Haraguchi: "A demonstration of a legal reasoning system based on teleological analogies"Proc.of the 7th Internatinal Conference on Artificial Intelligence and Law. 196-205 (1999)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] N.Morita, M.Hraguchi and Y.Okudo: "A Method of Similarity-Driven Knowledge Revision for Type Specializations"Lecture Notes in Artificial Intelligence. Vol.1720. 194-205 (1999)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] Y.Kudoh and M.Haraguchi: "An Appropriate Abstraction for an Attribute-Oriented Induction"Lecture Notes in Artificial Intelligence. Vol.1721. 43-55 (1999)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2000 Final Research Report Summary
  • [Publications] Y.Itoh and M.Haraguchi: "Conceptual Classifications Guided by a Concept Hierarchy"Lecture Notes in Artificial Intelligence. Vol.1968. 166-178 (2000)

    • Related Report
      2000 Annual Research Report
  • [Publications] M.Haraguchi: "Analogical Classification based on Abstraction"Proc. 17th Workshop on Machine Intelligence. 29-31 (2000)

    • Related Report
      2000 Annual Research Report
  • [Publications] 工藤嘉晃,原口誠: "適切な抽象化に基づくデータベースの一般化によるデータマイニング"人工知能学会誌. Vol.15,No.4. 638-648 (2000)

    • Related Report
      2000 Annual Research Report
  • [Publications] T.Kakuta, M.Haraguchi: "A demonstration of a legal reasoning system based on teleological analogies"Proc.of the 7th Internatinal Conference on Artificial Intelligence and Law . 196-205 (1999)

    • Related Report
      2000 Annual Research Report
  • [Publications] N.Morita, M.Haraguchi and Y.Okudo: "A Method of Similarity-Driven Knowledge Revision for Type Specializations"Lecture Notes in Artificial Intelligence. Vol.1720. 194-205 (1999)

    • Related Report
      2000 Annual Research Report
  • [Publications] Y.Kudoh and M.Haraguchi: "An Appropriate Abstraction for an Attribute-Oriented Induction"Lecture Notes in Artificial Intelligence. Vol.1721. 43-55 (1999)

    • Related Report
      2000 Annual Research Report
  • [Publications] 原口誠,角田篤泰: "法律人工知能(吉野一編)「法の目的に適った法的類推の実現」(pp. 358-369)を分担執筆"創成社. 394 (2000)

    • Related Report
      2000 Annual Research Report
  • [Publications] T.Kakuta, M.Haraguchi: "A demonstration of a legal reasoning system based on teleological analogies"Proc. 7th International Conference on Artificial Intelligence and Law. 196-205 (1999)

    • Related Report
      1999 Annual Research Report
  • [Publications] N.MORITA, M.HARAGUCHI, Y.OKUBO: "A Method of Similarity-Driven Knowledge Revision for Type Specializations"Proc. 10th International Conference on Algorithmic Learning Theory. 194-205 (1999)

    • Related Report
      1999 Annual Research Report
  • [Publications] Y.KUDOH and M.HARAGUCHI: "An Appropriate Abstraction for an Attribute-Oriented Induction"Proc. 2nd International Conference on Discovery Science. 29-36 (1999)

    • Related Report
      1999 Annual Research Report

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Published: 1999-04-01   Modified: 2016-04-21  

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