Word sense disambiguation with pattern learning and automatic feature selection

Word sense disambiguation with pattern learning and automatic feature selection

This paper presents a novel approach for word sense disambiguation. The underlying algorithm has two main components: (1) pattern learning from available sense-tagged corpora (SemCor), from dictionary definitions (WordNet) and from a generated corpus (GenCor); and (2) instance based learning with automatic feature selection, when training data is available for a particular word. The ideas descr...

Pattern Learning and Active Feature Selection for Word Sense Disambiguation

We present here the main ideas of the algorithm employed in the SMUls and SMU aw systems. These systems have participated in the SENSEVAL-2 competition attaining the best performance for both English all words and English lexical sample tasks1. The algorithm has two main components (1) pattern learning from available sense tagged corpora (SemCor) and dictionary definitions (WordNet), and (2) in...

Transfer Learning, Feature Selection and Word Sense Disambiguation

We propose a novel approach for improving Feature Selection for Word Sense Disambiguation by incorporating a feature relevance prior for each word indicating which features are more likely to be selected. We use transfer of knowledge from similar words to learn this prior over the features, which permits us to learn higher accuracy models, particularly for the rarer word senses. Results on the ...

Instance Based Learning with Automatic Feature Selection Applied to Word Sense Disambiguation

Automatic Sense Disambiguation for Target Word Selection

This paper describes a method of automatic sense disambiguation for target word selection in Korean to English machine translation. At first, we define the concept of cluster for each sense of given verb according to corresponding target word. And then, we propose a method which selects the sense combination of words as the correct sense that has the greatest number of overlaps between input ca...