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 ...
This paper presents a graph-theoretical approach to lexical disambiguation on word co-occurrences. Producing a dictionary similar to WordNet, this method is the counterpart to word...
In this paper we report the experiments for the CLEF 2009 Robust-WSD task, both for the monolingual (English) and the bilingual (Spanish to English) subtasks. Our main experimenta...
Abstract. Automated Text Categorization has reached the levels of accuracy of human experts. Provided that enough training data is available, it is possible to learn accurate autom...
Abstract. As any other classification task, Word Sense Disambiguation requires a large number of training examples. These examples, which are easily obtained for most of the tasks,...