An N-gram language model aims at capturing statistical word order dependency information from corpora. Although the concept of language models has been applied extensively to handl...
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...
Recent research works on unsupervised word sense disambiguation report an increase in performance, which reduces their handicap from the respective supervised approaches for the sa...
George Tsatsaronis, Iraklis Varlamis, Kjetil N&osl...
Past research has shown that dictionaries and glosses can be beneficial in computer assisted language learning, particularly in vocabulary learning. We propose that L2 vocabulary ...
This paper describes a set of comparative experiments, including cross{corpus evaluation, between ve alternative algorithms for supervised Word Sense Disambiguation (WSD), namely ...