On compiling queries in recursive first-order databases
Journal of the ACM (JACM)
On the implementation of a simple class of logic queries for databases
PODS '86 Proceedings of the fifth ACM SIGACT-SIGMOD symposium on Principles of database systems
Naive evaluation of recursively defined relations
On knowledge base management systems: integrating artificial intelligence and d atabase technologies
Magic sets and other strange ways to implement logic programs (extended abstract)
PODS '86 Proceedings of the fifth ACM SIGACT-SIGMOD symposium on Principles of database systems
An amateur's introduction to recursive query processing strategies
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
Efficient evaluation for a subset of recursive queries
PODS '87 Proceedings of the sixth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Worst-case complexity analysis of methods for logic query implementation
PODS '87 Proceedings of the sixth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Journal of Logic Programming
Efficient evaluation for a subset of recursive queries
Journal of Logic Programming
Proceedings of the Fifth International Conference on Data Engineering
Normalization of Linear Recursions in Deductive Databases
Proceedings of the Ninth International Conference on Data Engineering
Recursive Strategies for Answering Recursive Queries - The RQA/FQI Strategy
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Speeding up the counting method by computing heritage functions in topological order
ADBIS'97 Proceedings of the First East-European conference on Advances in Databases and Information systems
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Grahne et al. have presented a graph algorithm for a subset of recursive queries. This method consists of two phases. In the first phase, the method transforms a linear binary-chain program into a set of equations over expressions containing predicate symbols. In the second phase, a graph is constructed from the equations and the answers are produced by traversing the relevant paths. Here we describe a new algorithm which requires less time than the algorithm of Grahne et al. The key idea of the improvement is to reduce the search space that will be traversed when a query is invoked. Further, we speed up the evaluation of cyclic data by generating most answers directly in terms of the answers already found and the associated “path information” instead of traversing the corresponding paths as usual. In this way, our algorithm achieves a linear time complexity for both cyclic and non-cyclic data.