Towards a mathematical theory of machine discovery from facts
Theoretical Computer Science - Special issue on algorithmic learning theory
Inductive logic programming and knowledge discovery in databases
Advances in knowledge discovery and data mining
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Polynomial Time Inductive Inference of Regular Term Tree Languages from Positive Data
ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
Detecting Traffic Problems with ILP
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Extracting Characteristic Structures among Words in Semistructured Documents
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Ordered Term Tree Languages which Are Polynomial Time Inductively Inferable from Positive Data
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Polynomial Time Algorithms for Finding Unordered Tree Patterns with Internal Variables
FCT '01 Proceedings of the 13th International Symposium on Fundamentals of Computation Theory
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Learning Block-Preserving Outerplanar Graph Patterns and Its Application to Data Mining
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
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Graphs have enough richness and flexibility to express discrete structures hidden in a large amount of data. Some searching methods utilizing graph algorithmic techniques have been developed in Knowledge Discovery. A term graph, which is one of expressions for graph-structured data, is a hypergraph whose hyperedges are regarded as variables. Although term graphs can represent complicated patterns found from structured data, it is hard to do pattern match and pattern search in them. We have been studying subclasses of term graphs, called regular term trees, which are suited for expressing tree-like structured data. In this paper, we consider a matching problem for a regular term tree t and a standard tree T, which decides whether or not there exists a tree T′ such that T′ is isomorphic to T and T′ is obtained by replacing variables in t with some trees. First we show that the matching problem for a regular term tree and a tree is NP-complete even if each variable in the regular term tree contains only 4 vertices. Next we give a polynomial time algorithm for solving the matching problem for a regular term tree and a tree of bounded degree such that the regular term tree has only variables consisting the constant number of vertices greater than one. We also report some computational experiments and compare our algorithm with a naive algorithm.