Most word sense disambiguation (WSD) methods require large quantities of manually annotated training data and/or do not exploit fully the semantic relations of thesauri. We propos...
George Tsatsaronis, Michalis Vazirgiannis, Ion And...
Supervised learning methods for WSD yield better performance than unsupervised methods. Yet the availability of clean training data for the former is still a severe challenge. In ...
We present an automatic method for senselabeling of text in an unsupervised manner. The method makes use of distributionally similar words to derive an automatically labeled train...
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...