论文标题
基于方面的情感分析具有特定方面的意见跨度
Aspect Based Sentiment Analysis with Aspect-Specific Opinion Spans
论文作者
论文摘要
基于方面的情感分析预测给定方面的情感极性引起了广泛的关注。以前的基于注意力的模型强调使用方面语义来帮助提取分类的意见特征。但是，这些作品要么无法捕获整个意见跨度，要么无法捕获可变长度的意见跨度。在本文中，我们通过汇总多个线性链CRF来介绍一个整洁有效的结构化注意模型。这样的设计使模型可以提取特定方面的意见跨度，然后通过利用提取的意见特征来评估情感极性。四个数据集上的实验结果证明了所提出的模型的有效性，我们的分析表明，我们的模型可以捕获特定于方面的意见跨度。
Aspect based sentiment analysis, predicting sentiment polarity of given aspects, has drawn extensive attention. Previous attention-based models emphasize using aspect semantics to help extract opinion features for classification. However, these works are either not able to capture opinion spans as a whole, or not able to capture variable-length opinion spans. In this paper, we present a neat and effective structured attention model by aggregating multiple linear-chain CRFs. Such a design allows the model to extract aspect-specific opinion spans and then evaluate sentiment polarity by exploiting the extracted opinion features. The experimental results on four datasets demonstrate the effectiveness of the proposed model, and our analysis demonstrates that our model can capture aspect-specific opinion spans.
