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Querying multiple sets of discovered rules

Published: 23 July 2002 Publication History

Abstract

Rule mining is an important data mining task that has been applied to numerous real-world applications. Often a rule mining system generates a large number of rules and only a small subset of them is really useful in applications. Although there exist some systems allowing the user to query the discovered rules, they are less suitable for complex ad hoc querying of multiple data mining rulebases to retrieve interesting rules. In this paper, we propose a new powerful rule query language Rule-QL for querying multiple rulebases that is modeled after SQL and has rigorous theoretical foundations of a rule-based calculus. In particular, we first propose a rule-based calculus RC based on the first-order logic, and then present the language Rule-QL that is at least as expressive as the safe fragment of RC. We also propose a number of efficient query evaluation techniques for Rule-QL and test them experimentally on some representative queries to demonstrate the feasibility of Rule-QL.

Cited By

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  • (2019)A Higher-Order Calculus of Computational FieldsACM Transactions on Computational Logic10.1145/328595620:1(1-55)Online publication date: 4-Jan-2019
  • (2017)Collaborating around Digital TabletopsACM Transactions on Computer-Human Interaction10.1145/305855124:3(1-30)Online publication date: 26-May-2017
  • (2011)A comparative study of signature based indexes for efficient retrieval of temporal patternsProceedings of the International Conference & Workshop on Emerging Trends in Technology10.1145/1980022.1980104(382-387)Online publication date: 25-Feb-2011
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Published In

cover image ACM Conferences
KDD '02: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
July 2002
719 pages
ISBN:158113567X
DOI:10.1145/775047
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 July 2002

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Author Tags

  1. association rules
  2. data mining queries
  3. query evaluation
  4. query languages
  5. rulebases

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Acceptance Rates

KDD '02 Paper Acceptance Rate 44 of 307 submissions, 14%;
Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

View all
  • (2019)A Higher-Order Calculus of Computational FieldsACM Transactions on Computational Logic10.1145/328595620:1(1-55)Online publication date: 4-Jan-2019
  • (2017)Collaborating around Digital TabletopsACM Transactions on Computer-Human Interaction10.1145/305855124:3(1-30)Online publication date: 26-May-2017
  • (2011)A comparative study of signature based indexes for efficient retrieval of temporal patternsProceedings of the International Conference & Workshop on Emerging Trends in Technology10.1145/1980022.1980104(382-387)Online publication date: 25-Feb-2011
  • (2011)Association Rules and Sequential PatternsWeb Data Mining10.1007/978-3-642-19460-3_2(17-62)Online publication date: 15-Apr-2011
  • (2010)Redundancy, Deduction Schemes, and Minimum-Size Bases for Association RulesLogical Methods in Computer Science10.2168/LMCS-6(2:4)20106:2Online publication date: 27-Jun-2010
  • (2010)Data Mining Query LanguagesData Mining and Knowledge Discovery Handbook10.1007/978-0-387-09823-4_33(655-664)Online publication date: 7-Jul-2010
  • (2009)Finding Actionable Knowledge via Automated ComparisonProceedings of the 2009 IEEE International Conference on Data Engineering10.1109/ICDE.2009.135(1419-1430)Online publication date: 29-Mar-2009
  • (2008)Minimum-size bases of association rulesProceedings of the 2008th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I10.5555/3120828.3120856(86-101)Online publication date: 15-Sep-2008
  • (2008)Tutoring model for promoting teaching skills of computer science prospective teachersACM SIGCSE Bulletin10.1145/1597849.138434540:3(276-280)Online publication date: 30-Jun-2008
  • (2008)Improving student performance using automated testing of simulated digital logic circuitsACM SIGCSE Bulletin10.1145/1597849.138434240:3(265-270)Online publication date: 30-Jun-2008
  • Show More Cited By

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