Polysemy Detection in Distributed Representation of Word Sense
This work addresses the challenge of identifying polysemic words in natural language processing, but it appears incremental as it builds on existing distributed representation methods.
The authors tackled the problem of detecting polysemy in word embeddings by proposing a statistical test based on fluctuations in neighboring word senses, and they explained a method to detect the effect of polysemy on vector positions.
In this paper, we propose a statistical test to determine whether a given word is used as a polysemic word or not. The statistic of the word in this test roughly corresponds to the fluctuation in the senses of the neighboring words a nd the word itself. Even though the sense of a word corresponds to a single vector, we discuss how polysemy of the words affects the position of vectors. Finally, we also explain the method to detect this effect.