Abstract. Most common feature selection techniques for document categorization are supervised and require lots of training data in order to accurately capture the descriptive and d...
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
We explore the problem of resolving the second person English pronoun you in multi-party dialogue, using a combination of linguistic and visual features. First, we distinguish gen...
We present a machine translation framework that can incorporate arbitrary features of both input and output sentences. The core of the approach is a novel decoder based on lattice...
In this paper we develop an approach to tackle the problem of verb selection for learners of English as a second language (ESL) by using features from the output of Semantic Role ...
Xiaohua Liu, Bo Han, Kuan Li, Stephan Hyeonjun Sti...