@inproceedings{grishin-2018-igevorse,
title = "Igevorse at {S}em{E}val-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes",
author = "Grishin, Maxim",
editor = "Apidianaki, Marianna and
Mohammad, Saif M. and
May, Jonathan and
Shutova, Ekaterina and
Bethard, Steven and
Carpuat, Marine",
booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-1164",
doi = "10.18653/v1/S18-1164",
pages = "995--998",
abstract = "This paper presents a comparison of several approaches for capturing discriminative attributes and considers an impact of concatenation of several word embeddings of different nature on the classification performance. A similarity-based method is proposed and compared with classical machine learning approaches. It is shown that this method outperforms others on all the considered word vector models and there is a performance increase when concatenated datasets are used.",
}
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%0 Conference Proceedings
%T Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes
%A Grishin, Maxim
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F grishin-2018-igevorse
%X This paper presents a comparison of several approaches for capturing discriminative attributes and considers an impact of concatenation of several word embeddings of different nature on the classification performance. A similarity-based method is proposed and compared with classical machine learning approaches. It is shown that this method outperforms others on all the considered word vector models and there is a performance increase when concatenated datasets are used.
%R 10.18653/v1/S18-1164
%U https://aclanthology.org/S18-1164
%U https://doi.org/10.18653/v1/S18-1164
%P 995-998
Markdown (Informal)
[Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes](https://aclanthology.org/S18-1164) (Grishin, SemEval 2018)
ACL