In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Parsing text to identify grammatical structure is a common task, especially in relation to programming languages and associated tools such as compilers. Parsers for context-free g...
Considering the difficulties inherent in the manual construction of natural language parsers, we have designed and implemented our system GRIND which is capable of learning a sequ...
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...