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CLT seminar: Mikael Kågebäck and Fredrik Johansson – Neural embeddings for automatic discovery of word senses (and new applications)

SEMINAR

Word sense induction (WSI) is the task of discovering word senses automatically, given a corpus. We propose a vector space model for WSI that leverages neural word embeddings, and the correlation statistics they capture, to compute high quality word instance embeddings. The instance embeddings are subsequently clustered to find the word senses present in the text. The model archives state of the art results on a well known dataset.

We expand on the idea of using neural embeddings for linguistic analysis by modelling temporal evolution and performing joint, comparative embedding of multiple corpora.

Date: 2015-02-26 10:30 - 12:00

Location: L308, Lennart Torstenssonsgatan 8

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Page updated: 2015-02-23 17:22

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