Papers by Martin Wegrzyn

1 papers
Exploring Semantic Spaces for Detecting Clustering and Switching in Verbal Fluency (2022.coling-1)

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Challenge: Existing evaluations of word/concept representations on verbal fluency tasks rely on human annotations of clusters and switches between sub-categories.
Approach: They analyze word/concept representations in an experimental verbal fluency dataset . they find that ConceptNet embeddings outperforms other semantic representations .
Outcome: The proposed method outperforms other semantic representations by a large margin.

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