Polynomial Time Inductive Inference of Ordered Tree Patterns with Internal Structured Variables from Positive Data

Abstract

Tree structured data such as HTML/XML files are represented by rooted trees with ordered children and edge labels. As a representation of a tree structured pattern in such tree structured data, we propose an ordered tree pattern, called a term tree, which is a rooted tree pattern consisting of ordered children and internal structured variables. A term tree is a generalization of standard tree patterns representing first order terms in formal logic. For a set of edge labels Λ and a term tree t, the term tree language of t, denoted by L _Λ(t), is the set of all labeled trees which are obtained from a term tree t by substituting arbitrary labeled trees for all variables in t. In this paper, we propose polynomial time algorithms for the following two problems for two fundamental classes of term trees. The membership problem is, given a term tree t and a tree T, to decide whether or not L _Λ(t) includes T. The minimal language problem is, given a set of labeled trees S, to find a term tree t such that L _Λ(t) is minimal among all term tree languages which contain all trees in S. Then, by using these two algorithms, we show that the two classes of term trees are polynomial time inductively inferable from positive data.