Word meaning ambiguity has always been an important problem in information retrieval and extraction, as well as, text mining (documents clustering and classification). Knowledge di...
Henryk Rybinski, Marzena Kryszkiewicz, Grzegorz Pr...
Word meaning disambiguation has always been an important problem in many computer science tasks, such as information retrieval and extraction. One of the problems, faced in automa...
Word sense discrimination is an unsupervised clustering problem, which seeks to discover which instances of a word/s are used in the same meaning. This is done strictly based on i...
Distributions of the senses of words are often highly skewed. This fact is exploited by word sense disambiguation (WSD) systems which back off to the predominant (most frequent) s...
Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...