Wrapper Induction: Learning (k,l)-Contextual Tree Languages Directly as Unranked Tree Automata

A (k, l)-contextual tree language can be learned from positive examples only; such languages have been successfully used as wrappers for information extraction from web pages. This paper shows how to represent the wrapper as an unranked tree automaton and how to construct it directly from the examples instead of using the (k, l)-forks of the examples. The former speeds up the extraction, the latter speeds up the learning.