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        <title>Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion</title>
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            <namePart type="given">Anna</namePart>
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    <abstract>In this paper, we present a novel algorithm that combines multi-context term embeddings using a neural classifier and we test this approach on the use case of corpus-based term set expansion. In addition, we present a novel and unique dataset for intrinsic evaluation of corpus-based term set expansion algorithms. We show that, over this dataset, our algorithm provides up to 5 mean average precision points over the best baseline.</abstract>
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%0 Conference Proceedings
%T Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion
%A Mamou, Jonathan
%A Pereg, Oren
%A Wasserblat, Moshe
%A Dagan, Ido
%Y Rogers, Anna
%Y Drozd, Aleksandr
%Y Rumshisky, Anna
%Y Goldberg, Yoav
%S Proceedings of the 3rd Workshop on Evaluating Vector Space Representations for NLP
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, USA
%F mamou-etal-2019-multi
%X In this paper, we present a novel algorithm that combines multi-context term embeddings using a neural classifier and we test this approach on the use case of corpus-based term set expansion. In addition, we present a novel and unique dataset for intrinsic evaluation of corpus-based term set expansion algorithms. We show that, over this dataset, our algorithm provides up to 5 mean average precision points over the best baseline.
%R 10.18653/v1/W19-2013
%U https://aclanthology.org/W19-2013/
%U https://doi.org/10.18653/v1/W19-2013
%P 95-101

Markdown (Informal)

[Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion](https://aclanthology.org/W19-2013/) (Mamou et al., RepEval 2019)

• Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion (Mamou et al., RepEval 2019)

ACL

• Jonathan Mamou, Oren Pereg, Moshe Wasserblat, and Ido Dagan. 2019. Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion. In Proceedings of the 3rd Workshop on Evaluating Vector Space Representations for NLP, pages 95–101, Minneapolis, USA. Association for Computational Linguistics.