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Studies on Time Complexity for Computing Association Rules in Data Mining

Research Project

Project/Area Number 13680446
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionNARA INSTITUTE OF SCIENCE AND TECHNOLOGY

Principal Investigator

ITO Minoru  Nara Institute of Science and Technology, Graduate School of Information Sciences, Professor, 情報科学研究科, 教授 (90127184)

Co-Investigator(Kenkyū-buntansha) SHIBATA Naoki  Nara Institute of Science and Technology, Graduate School of Information Sciences, Assistant Professor, 情報科学研究科, 助手 (40335477)
YASUMOTO Keiichi  Nara Institute of Science and Technology, Graduate School of Information Sciences, Associate Professor, 情報科学研究科, 助教授 (40273396)
石井 信  奈良先端科学技術大学院大学, 情報科学研究科, 教授 (90294280)
Project Period (FY) 2001 – 2002
Project Status Completed (Fiscal Year 2002)
Budget Amount *help
¥2,800,000 (Direct Cost: ¥2,800,000)
Fiscal Year 2002: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2001: ¥1,800,000 (Direct Cost: ¥1,800,000)
KeywordsData Mining / Association Rule / NP-complete problem / NP完全
Research Abstract

1. Computing association rules for market basket database is one of the most fundamental problems in data mining. An association rule is a statement of the form X⇒Y, whose intuitive meaning is that if a customer buys all the items in X, then he is also likely to buy all the items in Y. In order that the association rule is meaningful, it is necessary that (a) the itemset X∪Y is large, (b) the rule is confident, and (c) the left side Y contains enough items. The algorithm for computing association rules consists of the two parts: first, computing a large itemset Z, and then dividing the set Z into X and Y such that X⇒Y is meaningful.
2. We introduced a rare itemset that is a dual concept for a large itemset, and proved that it is NP-complete to decide if there is a large itemset whose size is smaller than a given size.
3. By transforming the rare itemset problem above into a problem for deciding if a meaningful association rule can be obtained from a given large itemset, we proved that the problem for computing a meaningful association rule is NP-complete.
4. We obtained a sufficient condition to compute a rare itemset in polynomial time.
5. Using the sufficient condition above, we obtained a subclass of databases in which a meaningful association rule can be computed in polynomial time.

Report

(3 results)
  • 2002 Annual Research Report   Final Research Report Summary
  • 2001 Annual Research Report
  • Research Products

    (20 results)

All Other

All Publications (20 results)

  • [Publications] Yoshihiro Murata: "An Approximation Algorithm for the Task-Coalition Problem"IEICE Transactions on Information and Systems. E85-D,4. 685-693 (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yasunori Ishihara: "Refinement of Complexity Results on Type Consistency for Object-Oriented Databases"Journal of Computer and System Sciences. 62,4. 537-564 (2001)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Shogo Shimizu: "Complexity of the Type-Consistency Problem for Acyclic Object-Oriented Database Schemas"IEICE Transactions on Information and Systems. E84-D,5. 623-634 (2001)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshihiro Murata: "Agent Oriented Self Adaptive Genetic Algorithm"Proc.IASTED Int.Conf.Communications and Computer Networks. 348-353 (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] 長行 康男: "マルチエージェント強化学習:未来状態の予測に基づいた接近法"情報処理学会数理モデル化と問題解決研究会. 42-6. 21-24 (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] 長行 康男: "マルコフゲームにおける環境モデルの推定を利用したマルチエージェント強化学習法"電子情報通信学会技術研究報告. AI2001-15. 29-36 (2001)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshihiro Murata: "An Approximation Algorithm for the Task-Coalition Problem"IEICE Transactions on Information and Systems. E85-D. 685-693 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yasunori Ishihara: "Refinement of Complexity Results on Type Consistency for Object-Oriented Databases"Journal of Computer and System Sciences. 62. 537-564 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Shogo Shimizu: "Complexity of the Type-Consistency Problem for Acylic Object-Oriented Database Schemas"IEICE Transactions on Information and Systems. E84-D. 623-634 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yoshihiro Murata: "Agent Oriented Self Adaptive Genetic Algorithm"Proc. IASTED Int. Conf. Communications and Computer Networks. 348-353 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yasuo Nagayuki: "Multi-Agent Reinforcement Learning: an Approach Based on the Estimation of the Future States Method for Markov Games: an Approach Based on the Estimation of the Environmental Model"IPSJ Technical Report on Mathematical Modeling and Problem Solving. 42-6. 21-24 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] Yasuo Nagayuki: "Multi-Agent Reinforcement Learning Method for Markov Games: an Approach Based on the Estimation of the Environmental Model"Technical Report of IECE. AI2001-45. 29-36 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2002 Final Research Report Summary
  • [Publications] 村田 佳洋: "エージェント指向自己適応遺伝アルゴリズム"情報処理学会論文誌「数理モデル化と応用」. (採録決定). (2003)

    • Related Report
      2002 Annual Research Report
  • [Publications] Yoshihiro Murata: "An Approximation Algorithm for the Task-Coalition Assignment Problem"IEICE Transactions on Information and Systems. 85-D, No.4. 685-693 (2002)

    • Related Report
      2002 Annual Research Report
  • [Publications] Yoshihiro Murata: "Agent Oriented Self Adaptive Genetic Algorithm"Proc. IASTED Int. Conf. Communications and Computer Networks. 348-353 (2002)

    • Related Report
      2002 Annual Research Report
  • [Publications] Shougo Shimizu: "Complexity of the type-consistency Problem for Acyclic Object-Oriented Database Schemes"IEICE Transactions on Information and Systems. E84-D・5. 623-634 (2001)

    • Related Report
      2001 Annual Research Report
  • [Publications] 長行 康男: "マルコフゲームにおける環境モデルの推定を利用したマルチエージェント強化学習法"電子情報通信学会技術研究報告. AI2001-15. 29-36 (2001)

    • Related Report
      2001 Annual Research Report
  • [Publications] 長行 康男: "未来状態の予測を利用したマルチエージェント強化学習法"第10回マルチエージェンと協調計算ワークショップ論文集. 85-90 (2001)

    • Related Report
      2001 Annual Research Report
  • [Publications] 芝山 敏満: "インクリメンタルサポートベクターマシンによる価値関数の学習"電子情報通信学会技術研究報告. NC2001-72. 13-18 (2001)

    • Related Report
      2001 Annual Research Report
  • [Publications] 稲垣 浩司: "他エージェントの行動予測を利用したマルチエージェント強化学習の状態空間分割による高速化"第14回自律分散システム・シンポジウム資料. 89-94 (2002)

    • Related Report
      2001 Annual Research Report

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Published: 2001-04-01   Modified: 2016-04-21  

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