论文标题
用非时空机制为基于方面的情感分析建模互惠依赖性
Modeling Inter-Aspect Dependencies with a Non-temporal Mechanism for Aspect-Based Sentiment Analysis
论文作者
论文摘要
对于基于方面的情感分析（ABSA）的多个方面，现有方法通常忽略了跨观察关系或依靠时间依赖来处理句子中各个方面的方面意识表示表示。尽管句子的多个方面出现在非附近的顺序中，但它们并不是在自然语言序列中严格的时间关系，因此不应将方面感知的句子表示为时间依赖性处理。在本文中，我们提出了一种新型的非时空机制，以通过建模相互依赖性来增强ABSA任务。此外，我们将重点放在众所周知的阶级不平衡问题上，并通过减少分配给分类良好的实例的损失来解决它。 Semeval 2014 Task 4的两个不同领域的实验证明了我们提出的方法的有效性。
For multiple aspects scenario of aspect-based sentiment analysis (ABSA), existing approaches typically ignore inter-aspect relations or rely on temporal dependencies to process aspect-aware representations of all aspects in a sentence. Although multiple aspects of a sentence appear in a non-adjacent sequential order, they are not in a strict temporal relationship as natural language sequence, thus the aspect-aware sentence representations should not be treated as temporal dependency processing. In this paper, we propose a novel non-temporal mechanism to enhance the ABSA task through modeling inter-aspect dependencies. Furthermore, we focus on the well-known class imbalance issue on the ABSA task and address it by down-weighting the loss assigned to well-classified instances. Experiments on two distinct domains of SemEval 2014 task 4 demonstrate the effectiveness of our proposed approach.
