In this paper a novel solution to automatic and unsupervised word sense induction (WSI) is introduced. It represents an instantiation of the `one sense per collocation' obser...
This paper investigates the new problem of automatic sense induction for instance names using automatically extracted attribute sets. Several clustering strategies and data source...
Ricardo Martin-Brualla, Enrique Alfonseca, Marius ...
Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current stateof-the-art methods in taxonomy learning have d...
Word Sense Induction (WSI) is the task of identifying the different senses (uses) of a target word in a given text. Traditional graph-based approaches create and then cluster a gra...
This paper presents an algorithm for unsupervised noun sense induction, based on clustering of Web search results. The algorithm does not utilize labeled training instances or any...
Goldee Udani, Shachi Dave, Anthony Davis, Tim Sibl...