Efficient mining of association rules using closed itemset lattices
Information Systems
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
Essentials of Constraint Programming
Essentials of Constraint Programming
Essentials of Constraint Programming
Essentials of Constraint Programming
Automatic generation of rule-based constraint solvers over finite domains
ACM Transactions on Computational Logic (TOCL)
Firewall Design: Consistency, Completeness, and Compactness
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Automatic generation of CHR constraint solvers
Theory and Practice of Logic Programming
Chr(prism)-based probabilistic logic learning
Theory and Practice of Logic Programming
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Rule-based formalisms are ubiquitous in computer science. However, a difficulty that arises frequently when specifying or programming the rules is to determine which effects should be propagated by these rules. In this paper, we present a tool called ARM (Automatic Rule Miner) that generates rules for relations over finite domains. ARM offers a rich functionality to provide the user with the possibility of specifying the admissible syntactic forms of the rules. Furthermore, we show that our approach performs well on various examples, e.g. generation of firewall rules or generation of rule-based constraint solvers. Thus, it is suitable for users from different fields.