In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard probl...
Tree edit distance is one of the most frequently used distance measures for comparing trees. When using the tree edit distance, we need to determine the cost of each operation, bu...
We consider three natural models of random logarithmic depth decision trees over Boolean variables. We give an efficient algorithm that for each of these models learns all but an ...
Navigating through tree structures is a core operation in tree processing programs. Most notably, XML processing programs intensively use XPath, the path specification language t...
We develop new algorithms for learning monadic node selection queries in unranked trees from annotated examples, and apply them to visually interactive Web information extraction. ...