Learning Tree Languages

Abstract

Tree languages have proved to be a versatile and rewarding extension of the classical notion of string languages. Many nice applications have been established over the years, in areas such as Natural Language Processing, Information Extraction, and Computational Biology. Although some properties of string languages transfer easily to the tree case, in particular for regular languages, several computational aspects turn out to be harder. It is therefore both of theoretical and of practical interest to investigate how far and in what ways Grammatical Inference algorithms developed for the string case are applicable to trees. This chapter surveys known results in this direction. We begin by recalling the basics of tree language theory. Then, the most popular learning scenarios and algorithms are presented. Several applications of Grammatical Inference of tree languages are reviewed in some detail. We conclude by suggesting a number of directions for future research.

Exact Learning of Primitive Formal Systems Defining Labeled Ordered Tree Languages via Queries

“…Computational learning theory is studied in the field of foundations of computer science. In computational learning theory, the learnability of tree languages has been studied intensively [5]. We consider the problem of identifying an unknown tree language from a specified class of tree languages.…”