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首页> 外文会议>International conference on neural information processing;Annual conference of Asia-Pacific Neural Network Society >Opinion Knowledge Injection Network for Aspect Extraction
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Opinion Knowledge Injection Network for Aspect Extraction

机译：观点提取的观点知识注入网络

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摘要

Aspect term extraction (ATE) is to extract explicit aspect expressions from online reviews. This paper focused on the supervised extraction of aspect term. Previous models for ATE either ignored the opinion information or improperly utilized the opinion information with a high-coupling method. We proposed a model to perform ATE with the assistance of opinion knowledge, called opinion knowledge injection network. Specifically, the proposed model distills the opinion knowledge through the attention mechanism and joins it into each word to assist aspect extraction. The proposed model achieved surprisingly good results, improving 1.34% and 1.23% than the best results before respectively on the laptop and restaurant datasets, and reached state-of-the-art.
机译：方面术语提取（ATE）是从在线评论中提取明确的方面表达。本文着重于方面术语的监督提取。 ATE的先前模型要么忽略了意见信息，要么通过高耦合方法不适当地利用了意见信息。我们提出了一种在意见知识的帮助下执行ATE的模型，称为意见知识注入网络。具体而言，提出的模型通过注意力机制提取意见知识，并将其结合到每个单词中以帮助方面提取。所提出的模型取得了令人惊讶的良好结果，分别比笔记本电脑和餐厅数据集上的最佳结果分别提高了1.34％和1.23％，并达到了最新水平。

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