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Aspect-based Sentiment Analysis (ABSA) is a fine-grained opinion mining approach that identifies and classifies opinions associated with specific entities (aspects) or their categories within a sentence. Despite its rapid growth and broad…

计算与语言 · 计算机科学 2025-11-06 Yan Cathy Hua , Paul Denny , Jörg Wicker , Katerina Taškova

Since the dawn of the digitalisation era, customer feedback and online reviews are unequivocally major sources of insights for businesses. Consequently, conducting comparative analyses of such sources has become the de facto modus operandi…

Aspect-Based Sentiment Analysis (ABSA) deals with the extraction of sentiments and their targets. Collecting labeled data for this task in order to help neural networks generalize better can be laborious and time-consuming. As an…

机器学习 · 计算机科学 2020-10-26 Akbar Karimi , Leonardo Rossi , Andrea Prati

Aspect-based sentiment analysis (ABSA) aims to predict the sentiment towards a specific aspect in the text. However, existing ABSA test sets cannot be used to probe whether a model can distinguish the sentiment of the target aspect from the…

计算与语言 · 计算机科学 2020-10-29 Xiaoyu Xing , Zhijing Jin , Di Jin , Bingning Wang , Qi Zhang , Xuanjing Huang

Aspect based sentiment analysis (ABSA) deals with the identification of the sentiment polarity of a review sentence towards a given aspect. Deep Learning sequential models like RNN, LSTM, and GRU are current state-of-the-art methods for…

计算与语言 · 计算机科学 2022-08-05 Ashish Kumar , Vasundhra Dahiya , Aditi Sharan

Instruction tuning of language models has demonstrated the ability to enhance model generalization to unseen tasks via in-context learning using a few examples. However, typical supervised learning still requires a plethora of downstream…

Aspect-based Sentiment Analysis (ABSA) aims to identify the aspect terms, their corresponding sentiment polarities, and the opinion terms. There exist seven subtasks in ABSA. Most studies only focus on the subsets of these subtasks, which…

计算与语言 · 计算机科学 2021-06-09 Hang Yan , Junqi Dai , Tuo ji , Xipeng Qiu , Zheng Zhang

The topic of aspect-based sentiment analysis (ABSA) has been explored for a variety of industries, but it still remains much unexplored in finance. The recent release of data for an open challenge (FiQA) from the companion proceedings of…

计算与语言 · 计算机科学 2018-08-27 Steve Yang , Jason Rosenfeld , Jacques Makutonin

Aspect-based sentiment analysis (ABSA) task consists of three typical subtasks: aspect term extraction, opinion term extraction, and sentiment polarity classification. These three subtasks are usually performed jointly to save resources and…

计算与语言 · 计算机科学 2021-11-19 Hongjiang Jing , Zuchao Li , Hai Zhao , Shu Jiang

The increasing volume of online reviews has made possible the development of sentiment analysis models for determining the opinion of customers regarding different products and services. Until now, sentiment analysis has proven to be an…

计算与语言 · 计算机科学 2023-08-01 Elena-Simona Apostol , Alin-Georgian Pisică , Ciprian-Octavian Truică

Aspect-based sentiment analysis (ABSA) aims at extracting opinionated aspect terms in review texts and determining their sentiment polarities, which is widely studied in both academia and industry. As a fine-grained classification task, the…

人工智能 · 计算机科学 2023-08-17 Anguo Dong , Cuiyun Gao , Yan Jia , Qing Liao , Xuan Wang , Lei Wang , Jing Xiao

Recent neural-based aspect-based sentiment analysis approaches, though achieving promising improvement on benchmark datasets, have reported suffering from poor robustness when encountering confounder such as non-target aspects. In this…

计算与语言 · 计算机科学 2021-04-26 Zhen Bi , Ningyu Zhang , Ganqiang Ye , Haiyang Yu , Xi Chen , Huajun Chen

Aspect-based sentiment analysis (ABSA) is an important subtask of sentiment analysis, which aims to extract the aspects and predict their sentiments. Most existing studies focus on improving the performance of the target domain by…

计算与语言 · 计算机科学 2024-05-10 Xuanwen Ding , Jie Zhou , Liang Dou , Qin Chen , Yuanbin Wu , Chengcai Chen , Liang He

Aspect-based sentiment analysis (ABSA) and Targeted ASBA (TABSA) allow finer-grained inferences about sentiment to be drawn from the same text, depending on context. For example, a given text can have different targets (e.g., neighborhoods)…

计算与语言 · 计算机科学 2020-12-15 Zhengxuan Wu , Desmond C. Ong

Aspect based sentiment analysis (ABSA) involves three fundamental subtasks: aspect term extraction, opinion term extraction, and aspect-level sentiment classification. Early works only focused on solving one of these subtasks individually.…

计算与语言 · 计算机科学 2021-04-08 Yue Mao , Yi Shen , Chao Yu , Longjun Cai

Aspect-Based Sentiment Analysis (ABSA) is a fine-grained linguistics problem that entails the extraction of multifaceted aspects, opinions, and sentiments from the given text. Both standalone and compound ABSA tasks have been extensively…

计算与语言 · 计算机科学 2025-07-18 S M Rafiuddin , Mohammed Rakib , Sadia Kamal , Arunkumar Bagavathi

The state-of-the-art Aspect-based Sentiment Analysis (ABSA) approaches are mainly based on either detecting aspect terms and their corresponding sentiment polarities, or co-extracting aspect and opinion terms. However, the extraction of…

计算与语言 · 计算机科学 2020-11-03 Chen Zhang , Qiuchi Li , Dawei Song , Benyou Wang

Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify…

Aspect-based sentiment analysis (ABSA), a popular research area in NLP has two distinct parts -- aspect extraction (AE) and labeling the aspects with sentiment polarity (ALSA). Although distinct, these two tasks are highly correlated. The…

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis (ABSA), aiming to analyze and understand people's opinions at the aspect level, has been attracting considerable interest in the last decade. To handle…

计算与语言 · 计算机科学 2022-11-08 Wenxuan Zhang , Xin Li , Yang Deng , Lidong Bing , Wai Lam