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The core code of our proposed method for refining target embeddings.
This repository was used in our paper:
Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
Bin Liang, Jiachen Du, Ruifeng Xu*, Binyang Li, Hejiao Huang. Proceedings of ACL 2019
Please cite our paper and kindly give a star for this repository if you use this code.
./run.sh
An overall architecture of our proposed framework is as follow:
The BibTex of the citation is as follow:
@inproceedings{liang-etal-2019-context,
title = "Context-aware Embedding for Targeted Aspect-based Sentiment Analysis",
author = "Liang, Bin and
Du, Jiachen and
Xu, Ruifeng and
Li, Binyang and
Huang, Hejiao",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/P19-1462",
doi = "10.18653/v1/P19-1462",
pages = "4678--4683",
abstract = "Attention-based neural models were employed to detect the different aspects and sentiment polarities of the same target in targeted aspect-based sentiment analysis (TABSA). However, existing methods do not specifically pre-train reasonable embeddings for targets and aspects in TABSA. This may result in targets or aspects having the same vector representations in different contexts and losing the context-dependent information. To address this problem, we propose a novel method to refine the embeddings of targets and aspects. Such pivotal embedding refinement utilizes a sparse coefficient vector to adjust the embeddings of target and aspect from the context. Hence the embeddings of targets and aspects can be refined from the highly correlative words instead of using context-independent or randomly initialized vectors. Experiment results on two benchmark datasets show that our approach yields the state-of-the-art performance in TABSA task.",
}
Open Source Sentiment Analysis Algorithm inlcuding Aspect-Based Sentiment Analysis (-ABSA) and Emotion Cause Extraction (-ECE).
Pickle Raw token data Text CSV Python other
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