中文
相关论文

相关论文: Entity-Aspect-Opinion-Sentiment Quadruple Extracti…

200 篇论文

We present a neural framework for opinion summarization from online product reviews which is knowledge-lean and only requires light supervision (e.g., in the form of product domain labels and user-provided ratings). Our method combines two…

计算与语言 · 计算机科学 2018-08-28 Stefanos Angelidis , Mirella Lapata

The Web has become the main platform where people express their opinions about entities of interest and their associated aspects. Aspect-Based Sentiment Analysis (ABSA) aims to automatically compute the sentiment towards these aspects from…

计算与语言 · 计算机科学 2020-04-21 Maria Mihaela Trusca , Daan Wassenberg , Flavius Frasincar , Rommert Dekker

Aspect-based sentiment analysis (ABSA) aims to identify four sentiment elements, including aspect term, aspect category, opinion term, and sentiment polarity. These elements construct a complete picture of sentiments. The most challenging…

计算与语言 · 计算机科学 2026-02-09 Wenna Lai , Haoran Xie , Guandong Xu , Qing Li

Aspect-based Sentiment Analysis (ABSA) is a critical task in Natural Language Processing (NLP) that focuses on extracting sentiments related to specific aspects within a text, offering deep insights into customer opinions. Traditional…

Aspect-based sentiment analysis (ABSA) is a challenging task of extracting sentiments along with their corresponding aspects and opinion terms from the text. The inherent subjectivity of span annotation makes variability in the surface…

计算与语言 · 计算机科学 2025-02-13 Soyoung Yang , Hojun Cho , Jiyoung Lee , Sohee Yoon , Edward Choi , Jaegul Choo , Won Ik Cho

Aspect-based sentiment analysis (ABSA) is a crucial task in information extraction and sentiment analysis, aiming to identify aspects with associated sentiment elements in text. However, existing ABSA datasets are predominantly…

计算与语言 · 计算机科学 2025-09-10 Chengyan Wu , Bolei Ma , Yihong Liu , Zheyu Zhang , Ningyuan Deng , Yanshu Li , Baolan Chen , Yi Zhang , Yun Xue , Barbara Plank

One of the key tasks of sentiment analysis of product reviews is to extract product aspects or features that users have expressed opinions on. In this work, we focus on using supervised sequence labeling as the base approach to performing…

计算与语言 · 计算机科学 2016-12-26 Lei Shu , Bing Liu , Hu Xu , Annice Kim

Aspect-based sentiment analysis (ABSA) in natural language processing enables organizations to understand customer opinions on specific product aspects. While deep learning models are widely used for English ABSA, their application in…

计算与语言 · 计算机科学 2025-09-23 Salha Alyami , Amani Jamal , Areej Alhothali

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…

Opinion phrase extraction is one of the key tasks in fine-grained sentiment analysis. While opinion expressions could be generic subjective expressions, aspect specific opinion expressions contain both the aspect as well as the opinion…

计算与语言 · 计算机科学 2019-02-08 Abhishek Laddha , Arjun Mukherjee

Opinion Mining and Sentiment Analysis is a process of identifying opinions in large unstructured/structured data and then analysing polarity of those opinions. Opinion mining and sentiment analysis have found vast application in analysing…

信息检索 · 计算机科学 2014-05-30 Deepali Virmani , Vikrant Malhotra , Ridhi Tyagi

A new opinion extraction method is proposed to summarize unstructured, user-generated content (i.e., online customer reviews) in the fixed topic domains. To differentiate the current approach from other opinion extraction approaches, which…

计算与语言 · 计算机科学 2019-07-31 Jongho Im , Taikgun Song , Youngsu Lee , Jewoo Kim

In this paper, we present AILS-NTUA system for Track-A of SemEval-2026 Task 3 on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which encompasses three complementary problems: Dimensional Aspect Sentiment Regression (DimASR),…

Multimodal Aspect-Based Sentiment Analysis (MABSA) seeks to extract fine-grained information from image-text pairs to identify aspect terms and determine their sentiment polarity. However, existing approaches often fall short in…

计算与语言 · 计算机科学 2025-10-31 Hao Liu , Lijun He , Jiaxi Liang , Zhihan Ren , Haixia Bi , Fan Li

In this paper, we extend financial sentiment analysis~(FSA) to event-level since events usually serve as the subject of the sentiment in financial text. Though extracting events from the financial text may be conducive to accurate sentiment…

计算与语言 · 计算机科学 2024-11-28 Tianyu Chen , Yiming Zhang , Guoxin Yu , Dapeng Zhang , Li Zeng , Qing He , Xiang Ao

Aspect-based-sentiment-analysis (ABSA) is a fine-grained sentiment evaluation task, which analyzes the emotional polarity of the evaluation aspects. Generally, the emotional polarity of an aspect exists in the corresponding opinion…

计算与语言 · 计算机科学 2023-10-10 Dongming Wu , Lulu Wen , Chao Chen , Zhaoshu Shi

Aspect Sentiment Triple Extraction (ASTE) is an emerging task in fine-grained sentiment analysis. Recent studies have employed Graph Neural Networks (GNN) to model the syntax-semantic relationships inherent in triplet elements. However,…

计算与语言 · 计算机科学 2024-02-26 Xiaowei Zhao , Yong Zhou , Xiujuan Xu

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 sentiment triplet extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences. Since the initial datasets used to evaluate models on ASTE had flaws, several studies later corrected the initial…

计算与语言 · 计算机科学 2022-12-20 Yuncong Li , Fang Wang , Sheng-Hua Zhong

Aspect-based sentiment analysis (ABSA) task is a multi-grained task of natural language processing and consists of two subtasks: aspect term extraction (ATE) and aspect polarity classification (APC). Most of the existing work focuses on the…

计算与语言 · 计算机科学 2020-02-13 Heng Yang , Biqing Zeng , JianHao Yang , Youwei Song , Ruyang Xu