Convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (NLP) tasks. Experiments have, howev...
There has been increasing number of independently proposed randomization methods in different stages of decision tree construction to build multiple trees. Randomized decision tre...
Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Y...
We present a revision learning model for improving the accuracy of a dependency parser. The revision stage corrects the output of the base parser by means of revision rules learne...
Decision tree induction techniques attempt to find small trees that fit a training set of data. This preference for smaller trees, which provides a learning bias, is often justifie...
Christian Bessiere, Emmanuel Hebrard, Barry O'Sull...
In this paper, we present a parser based on a stochastic structured language model (SLM) with a
exible history reference mechanism. An SLM is an alternative to an n-gram model as...