document: In the paper we present an extended version of the graph-based unsupervised Word Sense Disambiguation algorithm. The algorithm is based on the spreading activation scheme applied to the graphs dynamically built on the basis of the text words and a large wordnet. The algorithm, originally proposed for English and Princeton WordNet, was adapted to Polish and plWordNet. An extension based on the knowledge acquired from the corpus-derived Measure of Semantic Relatedness was proposed. The extended algorithm was evaluated against the manually disambiguated corpus. We observed improvement in the case of the disambiguation performed for shorter text contexts. In addition the algorithm application expressed improvement in document clustering task.
doc_bio_tags: O O O O O O O O O O O O O O B B O B O O O O B I I O O O O O O O O O O O B I O O B I O B O O O B I I I O O O B I I O B O O O O O O O O O O O O O O O O B O O O O B I I O O O O O O O O B O O O O O O O O B O O O O B I I
extractive_keyphrases: algorithm disambiguation document clustering task english and princeton wordnet extension large wordnet manually disambiguated corpus polish and plwordnet spreading activation scheme text words
abstractive_keyphrases: built on the basis of the text words and a large wordne corpus-derived measure of semantic relatedness extended algorithm extended version of the graph-based unsupervised word sense disambiguation algorithm word sense disambiguation algorithm