Deep transfer learning mechanism for fine-grained cross-domain sentiment classification
Z Cao, Y Zhou, A Yang, S Peng - Connection Science, 2021 - Taylor & Francis
The goal of cross-domain sentiment classification is to utilise useful information in the source
domain to help classify sentiment polarity in the target domain, which has a large number of …
domain to help classify sentiment polarity in the target domain, which has a large number of …
Determination of effective management strategies for scenic area emergencies using association rule mining
Y Shi, B Wu, N Chen, A Chen, J Li, H Li - International Journal of Disaster …, 2019 - Elsevier
Appropriately handling unexpected events during the construction, development, and
operation stages of scenic areas and ensuring the personal and property safety of tourists …
operation stages of scenic areas and ensuring the personal and property safety of tourists …
Research progress on cross-domain text sentiment classification
赵传君， 王素格， 李德玉 - Journal of Software, 2020 - jos.org.cn
作为社会媒体文本情感分析的重要的文本情感分类任务, 其可以有效缓解目标领域 (1)
按照目标领域中是否有带标签数据, 可分为直推式和归纳迁移方法, 模型迁移方法 …
按照目标领域中是否有带标签数据, 可分为直推式和归纳迁移方法, 模型迁移方法 …
跨领域文本情感分类研究进展
赵传君， 王素格， 李德玉 - 软件学报, 2020 - jos.org.cn
作为社会媒体文本情感分析的重要的文本情感分类任务, 其可以有效缓解目标领域(1)
按照目标领域中是否有带标签数据, 可分为直推式和归纳迁移方法, 模型迁移方法 …
按照目标领域中是否有带标签数据, 可分为直推式和归纳迁移方法, 模型迁移方法 …
Sentiment classification of news text data using intelligent model
S Zhang - Frontiers in Psychology, 2021 - frontiersin.org
Text sentiment classification is a fundamental sub-area in natural language processing. The
sentiment classification algorithm is highly domain-dependent. For example, the phrase …
sentiment classification algorithm is highly domain-dependent. For example, the phrase …
NLWSNet: a weakly supervised network for visual sentiment analysis in mislabeled web images
Large-scale datasets are driving the rapid developments of deep convolutional neural
networks for visual sentiment analysis. However, the annotation of large-scale datasets is …
networks for visual sentiment analysis. However, the annotation of large-scale datasets is …
Domain-invariant representation learning using an unsupervised domain adversarial adaptation deep neural network
Abstract Domain adaptation is proposed to improve the recognition performance of the
domain shift or the dataset bias. The domain shift is a very common problem, which is …
domain shift or the dataset bias. The domain shift is a very common problem, which is …
Cross lingual sentiment analysis: a clustering-based bee colony instance selection and target-based feature weighting approach
The lack of sentiment resources in poor resource languages poses challenges for the
sentiment analysis in which machine learning is involved. Cross-lingual and semi …
sentiment analysis in which machine learning is involved. Cross-lingual and semi …
Single-Source Domain Adaptation for Emotion Classification Using CNN and Broad Learning
S Peng, L Cao - Textual Emotion Classification Using Deep Broad …, 2024 - Springer
Single-source domain adaptation (SSDA) for emotion classification aims to leverage useful
information in a source domain to help predict emotional polarity in a target domain in a …
information in a source domain to help predict emotional polarity in a target domain in a …
An attention network based on feature sequences for cross-domain sentiment classification
J Meng, Y Dong, Y Long, D Zhao - Intelligent Data Analysis, 2021 - content.iospress.com
The difficulty of cross-domain text sentiment classification is that the data distributions in the
source domain and the target domain are inconsistent. This paper proposes an attention …
source domain and the target domain are inconsistent. This paper proposes an attention …