Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Linear-time modular decomposition and efficient transitive orientation of comparability graphs
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Computational properties of metaquerying problems
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
IEEE Transactions on Knowledge and Data Engineering
Computational properties of metaquerying problems
ACM Transactions on Computational Logic (TOCL)
Towards Efficient Metaquerying
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A New Linear Algorithm for Modular Decomposition
CAAP '94 Proceedings of the 19th International Colloquium on Trees in Algebra and Programming
FlexiMine – A Flexible Platform for KDD Research and Application Development
Annals of Mathematics and Artificial Intelligence
Optimal implementation of conjunctive queries in relational data bases
STOC '77 Proceedings of the ninth annual ACM symposium on Theory of computing
Linear time algorithm for isomorphism of planar graphs (Preliminary Report)
STOC '74 Proceedings of the sixth annual ACM symposium on Theory of computing
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Metaqueries: semantics, complexity, and efficient algorithms
Artificial Intelligence
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Metaquerying is a data mining technique by which hidden dependencies among several database relations can be discovered in the form of Datalog-like rules, and this technique has already been successfully applied to several real-world application domains. Unfortunately, recent papers have shown that performing metaquerying turns out to be in general quite demanding from the computational viewpoint. The aim of this paper is to illustrate techniques by which metaquerying can be answered as efficiently as possible. Therefore, we first provide some new results regarding the computation of the number of substitutions for a given metaquery. In particular, an important source of complexity of implementing metaquerying depends on the exponential number of variable substitutions potentially to be analyzed to compute results, many of which turn out to be actually redundant. Redundancy checks are therefore illustrated and exploited below in order to minimize the computational cost to be paid to implement metaquerying. Metaquerying result construction algorithms are then given.