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        <title>A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions</title>
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    <name type="personal">
        <namePart type="given">Navnita</namePart>
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            <title>Proceedings of the Australasian Language Technology Association Workshop 2018</title>
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            <namePart type="given">Xiuzhen</namePart>
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    <abstract>In this paper, we perform a comparative evaluation of off-the-shelf embedding models over the task of compositionality prediction of multiword expressions(“MWEs”). Our experimental results suggest that character- and document-level models capture knowledge of MWE compositionality and are effective in modelling varying levels of compositionality, with the advantage over word-level models that they do not require token-level identification of MWEs in the training corpus.</abstract>
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%0 Conference Proceedings
%T A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions
%A Nandakumar, Navnita
%A Salehi, Bahar
%A Baldwin, Timothy
%Y Kim, Sunghwan Mac
%Y Zhang, Xiuzhen (Jenny)
%S Proceedings of the Australasian Language Technology Association Workshop 2018
%D 2018
%8 December
%C Dunedin, New Zealand
%F nandakumar-etal-2018-comparative
%X In this paper, we perform a comparative evaluation of off-the-shelf embedding models over the task of compositionality prediction of multiword expressions(“MWEs”). Our experimental results suggest that character- and document-level models capture knowledge of MWE compositionality and are effective in modelling varying levels of compositionality, with the advantage over word-level models that they do not require token-level identification of MWEs in the training corpus.
%U https://aclanthology.org/U18-1009
%P 71-76

Markdown (Informal)

[A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions](https://aclanthology.org/U18-1009) (Nandakumar et al., ALTA 2018)

• A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions (Nandakumar et al., ALTA 2018)

ACL

• Navnita Nandakumar, Bahar Salehi, and Timothy Baldwin. 2018. A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions. In Proceedings of the Australasian Language Technology Association Workshop 2018, pages 71–76, Dunedin, New Zealand.