Results 1 to 10 of about 163,222 (131)
Modeling sentiment dependencies with graph convolutional networks for aspect-level sentiment classification [PDF]
Knowledge-Based Systems, 2020 Abstract Aspect-level sentiment classification aims to distinguish the sentiment polarities over one or more aspect terms in a sentence. Existing approaches mostly model different aspects in one sentence independently, which ignore the sentiment dependencies between different aspects. However, such dependency information between different aspects can
Linlin Hou
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Interactive Attention Networks for Aspect-Level Sentiment Classification [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Aspect-level sentiment classification aims at identifying the sentiment polarity of specific target in its context. Previous approaches have realized the importance of targets in sentiment classification and developed various methods with the goal of ...
Li, Sujian +3 more
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IEEE Access, 2019 Aspect-level sentiment classification is a fine-grained sentiment analysis task. It aims to predict the sentiment of a review in different aspects. Recently many works exploit the hierarchical attention network to capture the aspect-specific sentiment ...
Yang Gao, Jianxun Liu, Pei Li, Dong Zhou
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Arabic aspect sentiment polarity classification using BERT
Journal of Big Data, 2022 Aspect-based sentiment analysis (ABSA) is a textual analysis methodology that defines the polarity of opinions on certain aspects related to specific targets. The majority of research on ABSA is in English, with a small amount of work available in Arabic.
Mohammed M. Abdelgwad +2 more
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A Survey on Aspect-Based Sentiment Classification [PDF]
ACM Computing Surveys, 2022 With the constantly growing number of reviews and other sentiment-bearing texts on the Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect-based sentiment classification (ABSC) allows for the automatic extraction of highly fine-grained sentiment information from text documents or sentences.
Gianni Brauwers, Flavius Frasincar
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Aspect-based sentiment classification model employing whale-optimized adaptive neural network [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2021 Nowadays in e-commerce applications, aspect-based sentiment analysis has become vital, and every consumer started focusing on various aspects of the product before making the purchasing decision on online portals like Amazon, Walmart, Alibaba, etc. Hence,
Nallathambi Balaganesh, K. Muneeswaran
doaj +1 more source
Performance analysis of aspect-level sentiment classification task based on different deep learning models [PDF]
PeerJ Computer Science, 2023 Aspect-level sentiment classification task (ASCT) is a natural language processing task that aims to correctly identify specific aspects and determine their sentiment polarity from a given target sentence.
Feifei Cao, Xiaomin Huang
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Sentiment Classification Method Based on BLSTM and Aspect Attention Module [PDF]
Jisuanji gongcheng, 2020 Aspect-Based Sentiment Analysis(ABSA) has been widely used in text information mining,but can hardly extract accurate feature information when the sentiment polarity of a sentence is fuzzy or a sentence has sentiment polarities of multiple aspects,which ...
PENG Zhuliang, LIU Bowen, FAN Cheng'an, WANG Jie, XIAO Ming, LIAO Zeen
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Aspect-based Sentiment Analysis Based on Dual-channel Graph Convolutional Network with Sentiment Knowledge [PDF]
Jisuanji kexue, 2023 Aspect-based sentiment analysis is a fine-grained sentiment analysis task whose goal is to classify the sentiment polarity of the given aspect terms in a sentence.Most of the current sentiment classification models build a graph neural network on the ...
YANG Ying, ZHANG Fan, LI Tianrui
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Multitask Learning for Aspect-Based Sentiment Classification [PDF]
Scientific Programming, 2021 Aspect-level sentiment analysis identifies the sentiment polarity of aspect terms in complex sentences, which is useful in a wide range of applications. It is a highly challenging task and attracts the attention of many researchers in the natural language processing field.
Chunhua Yao +4 more
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