Zobrazeno 1 - 10
of 137
pro vyhledávání: '"aspect-based sentiment classification"'
Employing synthetic data for addressing the class imbalance in aspect-based sentiment classification
Publikováno v:
Journal of Information and Telecommunication, Vol 8, Iss 2, Pp 167-188 (2024)
ABSTRACTThe class imbalance problem, in which the distribution of different classes in training data is unequal or skewed, is a prevailing problem. This can lead to classifier algorithms being biased, negatively impacting the performance of the minor
Externí odkaz:
https://doaj.org/article/91b27d80c89242af8a10013a1589bd7d
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 10, Pp 18566-18591 (2023)
Aspect-based sentiment analysis (ABSA) is a fine-grained and diverse task in natural language processing. Existing deep learning models for ABSA face the challenge of balancing the demand for finer granularity in sentiment analysis with the scarcity
Externí odkaz:
https://doaj.org/article/43c66d43fb0d472a9274a1cddb4e7e07
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
Introduction: Aspect-based sentiment classification is a fine-grained sentiment classification task. State-of-the-art approaches in this field leverage graph neural networks to integrate sentence syntax dependency. However, current methods fail to ex
Externí odkaz:
https://doaj.org/article/df1527e9cb234e719bd8773185c90430
Publikováno v:
IEEE Access, Vol 11, Pp 34990-34998 (2023)
Aspect-level sentiment classification (ASC) is a fine-grained sentiment analysis task that involves detecting the sentiment polarity of a specific opinion target in a given sentence. Despite the popularity of deep learning methods, the limited availa
Externí odkaz:
https://doaj.org/article/7966d3687d4f4c7e9ec59fccd52b6ce4
Autor:
Feifei Cao, Xiaomin Huang
Publikováno v:
PeerJ Computer Science, Vol 9, p e1578 (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. Deep learning models have been proven to be
Externí odkaz:
https://doaj.org/article/82a40de4812d4e959cb7e227f01274ca
One critical aspect that remains in the application of state-of-the-art neural networks to text analysis in applied research is the continued requirement for manual data annotation. In computer science research, there is a strong focus on maximizing
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A92377
https://ul.qucosa.de/api/qucosa%3A92377/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A92377/attachment/ATT-0/
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 53, Iss 2, Pp 248-256 (2022)
We proposed Reinforced Dependency Graph for Aspect-based Sentiment Classification (RDGSC), a reinforced dependency graph model for aspect-based sentiment classification. In this framework, we train a policy network using deep reinforcement learning a
Externí odkaz:
https://doaj.org/article/5711b79847e74122b63d444a0d826705
Publikováno v:
Jisuanji kexue, Vol 49, Iss 3, Pp 294-300 (2022)
Aspect-based sentiment classification aims at identifying the sentiment polarity of the given aspect in a sentence.Most of the previous methods are based on long short-term memory network(LSTM)and attention mechanisms,which largely rely on the semant
Externí odkaz:
https://doaj.org/article/b4420a9bbd8947b197a4ef5b5c972ead
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