The performance of any word recognizer depends on the lexicon presented. Usually large lexicons or lexicons containing similar entries pose greater difficulty for recognizers. How...
We present a quantitative model of word order and movement constraints that enables a simple and uniform treatment of a seemingly heterogeneous collection of linear order phenomena...
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
We propose a self-supervised word-segmentation technique for Chinese information retrieval. This method combines the advantages of traditional dictionary based approaches with cha...
Fuchun Peng, Xiangji Huang, Dale Schuurmans, Nick ...