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Querying multiple sets of discovered rules
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Source International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
Edmonton, Alberta, Canada
SESSION: Frequent patterns I table of contents
Pages: 52 - 60  
Year of Publication: 2002
ISBN:1-58113-567-X
Authors
Alexander Tuzhilin  New York University, New York, NY
Bing Liu  National University of Singapore, Singapore
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SIGMOD: ACM Special Interest Group on Management of Data
: AAAI
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 43,   Citation Count: 11
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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  11

Collaborative Colleagues:
Alexander Tuzhilin: colleagues
Bing Liu: colleagues