Jian Zhongquan, Li Jiajian, Wang Meihong, Yao Junfeng, Wu Qingqiang
Institute of Artificial Intelligence, Xiamen University, Xiamen, 361005, Fujian, China.
School of Informatics, Xiamen University, Xiamen, 361005, Fujian, China.
Neural Netw. 2025 Nov;191:107758. doi: 10.1016/j.neunet.2025.107758. Epub 2025 Jul 4.
Aspect-Level Sentiment Classification (ALSC) is a fine-grained Sentiment Analysis (SA) task that aims to determine the sentiments of a sentence toward different aspects. Despite their significant success, most existing methods derive aspect sentiment semantics from individual sentences, overlooking the interrelationships among relevant sentences that could provide a more comprehensive understanding of aspect sentiment semantics. To this end, we propose AspLearn, an aspect-learning method to optimize aspect sentiment semantics and generate more robust aspect-specific sentence features for the ALSC task. In a nutshell, AspLearn employs the Aspect-aware Contrastive Learning (AspCL) to mine valuable aspect-related knowledge from aspect-relevant samples, thereby optimizing aspect sentiment semantics and enhancing the model's performance. AspLearn is a simple yet effective method, with its superior aspect learning capabilities confirmed through extensive experiments on three benchmarks. Notably, AspLearn, using DeBERTa as the backbone, achieves Macro F1 score improvements of 3.13%, 0.76%, and 1.07% over the second-best results on the Laptops, Restaurants, and Twitter datasets, respectively. Furthermore, AspLearn's mechanism can retrieve the most relevant demonstrations for Large Language Models (LLMs), enhancing their sentiment recognition capabilities.
方面级情感分类（ALSC）是一项细粒度情感分析（SA）任务，旨在确定句子对不同方面的情感。尽管现有方法取得了显著成功，但大多数方法都是从单个句子中推导方面情感语义，忽略了相关句子之间的相互关系，而这些关系可以提供对方面情感语义更全面的理解。为此，我们提出了AspLearn，一种用于优化方面情感语义并为ALSC任务生成更强大的特定方面句子特征的方面学习方法。简而言之，AspLearn采用方面感知对比学习（AspCL）从与方面相关的样本中挖掘有价值的方面相关知识，从而优化方面情感语义并提高模型性能。AspLearn是一种简单而有效的方法，通过在三个基准上进行的广泛实验证实了其卓越的方面学习能力。值得注意的是，以DeBERTa为骨干的AspLearn在笔记本电脑、餐厅和推特数据集上分别比次优结果的宏观F1分数提高了3.13%、0.76%和1.07%。此外,AspLearn的机制可以为大语言模型（LLMs）检索最相关的示例，增强其情感识别能力。
