Search Results for author: N

Found 7 papers, 1 papers with code

How Well Do Embedding Models Capture Non-compositionality? A View from Multiword Expressions

no code implementations WS 2019 N, Navnita akumar, Timothy Baldwin, Bahar Salehi

In this paper, we apply various embedding methods on multiword expressions to study how well they capture the nuances of non-compositional data.

A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions

no code implementations ALTA 2018 N, Navnita akumar, Bahar Salehi, Timothy Baldwin

In this paper, we perform a comparative evaluation of off-the-shelf embedding models over the task of compositionality prediction of multiword expressions(``MWEs'').

Information Retrieval Word Embeddings

Semi-supervised Clustering of Medical Text

no code implementations WS 2016 Pracheta Sahoo, Asif Ekbal, Sriparna Saha, Diego Moll{\'a}, N, Kaushik an

Semi-supervised clustering is an attractive alternative for traditional (unsupervised) clustering in targeted applications.

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