@inproceedings{gencoglu-2020-sentence,
title = "Sentence Transformers and {B}ayesian Optimization for Adverse Drug Effect Detection from {T}witter",
author = "Gencoglu, Oguzhan",
booktitle = "Proceedings of the Fifth Social Media Mining for Health Applications Workshop {\&} Shared Task",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.smm4h-1.30",
pages = "161--164",
abstract = "This paper describes our approach for detecting adverse drug effect mentions on Twitter as part of the Social Media Mining for Health Applications (SMM4H) 2020, Shared Task 2. Our approach utilizes multilingual sentence embeddings (sentence-BERT) for representing tweets and Bayesian hyperparameter optimization of sample weighting parameter for counterbalancing high class imbalance.",
}
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%0 Conference Proceedings
%T Sentence Transformers and Bayesian Optimization for Adverse Drug Effect Detection from Twitter
%A Gencoglu, Oguzhan
%S Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task
%D 2020
%8 dec
%I Association for Computational Linguistics
%C Barcelona, Spain (Online)
%F gencoglu-2020-sentence
%X This paper describes our approach for detecting adverse drug effect mentions on Twitter as part of the Social Media Mining for Health Applications (SMM4H) 2020, Shared Task 2. Our approach utilizes multilingual sentence embeddings (sentence-BERT) for representing tweets and Bayesian hyperparameter optimization of sample weighting parameter for counterbalancing high class imbalance.
%U https://aclanthology.org/2020.smm4h-1.30
%P 161-164
Markdown (Informal)
[Sentence Transformers and Bayesian Optimization for Adverse Drug Effect Detection from Twitter](https://aclanthology.org/2020.smm4h-1.30) (Gencoglu, SMM4H 2020)
ACL