NSTL国家科技图书文献中心

1. Neurosymbolic AI for Personalized Sentiment Analysis NSTL国家科技图书文献中心

Luyao Zhu | Rui Mao ... - 《HCI International 2024 - Late Breaking Papers,Part IX》 - International Conference on Human-Computer Interaction - 2025, - 269～290 - 共22页

摘要：Sentiment analysis is crucial in extracting | refine sentiment* analysis algorithms, but there is a* | framework for personalized sentiment* analysis that* | performing sentiment* analysis. In particular, such* | valuable insights from vast amounts of textual data

关键词： Sentiment analysis | Personalization | Persona | Personality | AI | NLP

2. Multimodal sentiment analysis based on multiple attention NSTL国家科技图书文献中心

Hongbin Wang | Chun Ren ... - 《Engineering Applications of Artificial Intelligence》 - 2025,140(Jan.) - 109731.1～109731.10 - 共10页

摘要： sentiment analysis. Although the data types are different | a method named multimodal sentiment analysis* based* | , there are information expressing the same sentiment | , using sentiment* information as a guide to extract text* | and image features related to sentiment. Finally

关键词： Multimodal sentiment analysis | Multimodal interaction | Adaptive | Attention mechanism

3. Multimodal Sentiment Analysis: Recognizing Sentiment in Memes NSTL国家科技图书文献中心

Georgi Vankov | Dimitar Dimitrov ... - 《Artificial Intelligence: Methodology,Systems,and Applications》 - International Conference on Artificial Intelligence: Methodology,Systems,and Applications - 2025, - 1～11 - 共11页

摘要： become essential to discern the sentiment* of such* | media users. The paper focuses on the sentiment* of* | ., automatically assigning sentiment* labels based on different* | identifying sentiment. Our results show that multimodal | The usage of memes and other visual material

关键词： Multimodal sentiment analysis | Emotion recognition | Meme dataset

4. Towards Multimodal Sentiment Analysis Debiasing via Bias Purification NSTL国家科技图书文献中心

Dingkang Yang | Mingcheng Li ... - 《Computer Vision - ECCV 2024,Part LVIII》 - European Conference on Computer Vision - 2025, - 464～481 - 共18页

摘要：Multimodal Sentiment* Analysis (MSA) aims to* | Multimodal Counterfactual Inference Sentiment* (MCIS* | ) analysis* framework based on causality rather than* | understand human intentions by integrating emotion-related | clues from diverse modalities, such as visual

关键词： Sentiment analysis | Multimodal learning

5. Dialogue sentiment analysis based on dialogue structure pre-training NSTL国家科技图书文献中心

Liang Yang | Qi Yang ... - 《Multimedia systems》 - 2025,31(2) - 98.1～98.13 - 共13页

摘要：The task of dialogue sentiment* analysis aims* | propose a dialogue sentiment* analysis framework that* | to identify the sentiment* polarity of utterances in* | , and sentiment* shift detection. These tasks are* | logical relationships and sentiment* interactions. By*

关键词： Dialogue structure | Sentiment analysis | Pre-training model

6. An Image Text Sentiment Analysis Method Using Bimodal Attention Mechanism NSTL国家科技图书文献中心

Zhang, Huchao | Ai, Guojin - 《Journal of circuits, systems and computers》 - 2025,34(1) - 1.1～1.23 - 共23页

摘要： sentiment analysis methods that suffer from insufficient | multimodal image sentiment* analysis method that integrates* | -the-art multimodal image sentiment analysis | features, insufficient analysis* of semantic relationship* | accuracy of sentiment* classification. The experimental*

关键词： Image sentiment analysis | text sentiment analysis | RoBERTa model | transformer | decision fusion

7. An Innovative Sentiment Analysis Model for COVID-19 Tweets NSTL国家科技图书文献中心

Areeba Umair | Elio Masciari - 《Numerical Computations,Part III》 - International Conference on Numerical Computations: Theory and Algorithms - 2025, - 353～361 - 共9页

摘要： terrible pandemic that the WHO has declared. Sentiment | analysis is a vital technique for figuring out how people | embeddings, the research suggests a novel sentiment | analysis model for COVID-19 tweets using CT-BERT as a | -measure for positive and negative sentiment

关键词： Sentiment analysis | COVID-19 | BERT model

8. A Sentiment Analysis on Reviews of Italian Healthcare NSTL国家科技图书文献中心

Maria Chiara Martini... | Chiara Zucco - 《Numerical Computations,Part III》 - International Conference on Numerical Computations: Theory and Algorithms - 2025, - 332～337 - 共6页

摘要：Sentiment analysis is gaining prominence in | the VADER sentiment* analysis engine, to analyze* | Italy. Sentiment* polarity was extracted from each* | the evaluation of patient satisfaction within | healthcare environments. The present article takes

关键词： Text mining | Sentiment analysis | VADER | VADER-IT

9. Text-Dominant Interactive Attention for Cross-Modal Sentiment Analysis NSTL国家科技图书文献中心

Zebao Zhang | Shuang Yang ... - 《Pattern Recognition and Computer Vision,Part V》 - Chinese Conference on Pattern Recognition and Computer Vision - 2025, - 201～215 - 共15页

摘要：In today's era, Cross-modal Sentiment Analysis | sentiment analysis network (TDiA), which utilizes cross | uni-modal features for sentiment* analysis. In TDiA* | the publicly available cross-fmodal sentiment | analysis dataset MVSA.

关键词： Sentiment analysis | Cross-model | Attention mechanism | Semantic association

10. ConD2: Contrastive Decomposition Distilling for Multimodal Sentiment Analysis NSTL国家科技图书文献中心

Xi Yu | Wenti Huang ... - 《Pattern Recognition and Computer Vision,Part V》 - Chinese Conference on Pattern Recognition and Computer Vision - 2025, - 158～172 - 共15页

摘要：Multimodal Sentiment* Analysis (MSA) leverages* | multimodal signals to detect the sentiment* of a video clip* | Sentiment Information Representations (SIR). Additionally | . Despite the impressive performance of previous MSA | approaches, the issue of inherent multimodal representation

摘要：Sentiment analysis is crucial in extracting | refine sentiment* analysis algorithms, but there is a* | framework for personalized sentiment* analysis that* | performing sentiment* analysis. In particular, such* | valuable insights from vast amounts of textual data

关键词： Sentiment analysis | Personalization | Persona | Personality | AI | NLP

摘要： sentiment analysis. Although the data types are different | a method named multimodal sentiment analysis* based* | , there are information expressing the same sentiment | , using sentiment* information as a guide to extract text* | and image features related to sentiment. Finally

关键词： Multimodal sentiment analysis | Multimodal interaction | Adaptive | Attention mechanism

摘要： become essential to discern the sentiment* of such* | media users. The paper focuses on the sentiment* of* | ., automatically assigning sentiment* labels based on different* | identifying sentiment. Our results show that multimodal | The usage of memes and other visual material

关键词： Multimodal sentiment analysis | Emotion recognition | Meme dataset

摘要：Multimodal Sentiment* Analysis (MSA) aims to* | Multimodal Counterfactual Inference Sentiment* (MCIS* | ) analysis* framework based on causality rather than* | understand human intentions by integrating emotion-related | clues from diverse modalities, such as visual

关键词： Sentiment analysis | Multimodal learning

摘要：The task of dialogue sentiment* analysis aims* | propose a dialogue sentiment* analysis framework that* | to identify the sentiment* polarity of utterances in* | , and sentiment* shift detection. These tasks are* | logical relationships and sentiment* interactions. By*

关键词： Dialogue structure | Sentiment analysis | Pre-training model

摘要： sentiment analysis methods that suffer from insufficient | multimodal image sentiment* analysis method that integrates* | -the-art multimodal image sentiment analysis | features, insufficient analysis* of semantic relationship* | accuracy of sentiment* classification. The experimental*

关键词： Image sentiment analysis | text sentiment analysis | RoBERTa model | transformer | decision fusion

摘要： terrible pandemic that the WHO has declared. Sentiment | analysis is a vital technique for figuring out how people | embeddings, the research suggests a novel sentiment | analysis model for COVID-19 tweets using CT-BERT as a | -measure for positive and negative sentiment

关键词： Sentiment analysis | COVID-19 | BERT model

摘要：Sentiment analysis is gaining prominence in | the VADER sentiment* analysis engine, to analyze* | Italy. Sentiment* polarity was extracted from each* | the evaluation of patient satisfaction within | healthcare environments. The present article takes

关键词： Text mining | Sentiment analysis | VADER | VADER-IT

摘要：In today's era, Cross-modal Sentiment Analysis | sentiment analysis network (TDiA), which utilizes cross | uni-modal features for sentiment* analysis. In TDiA* | the publicly available cross-fmodal sentiment | analysis dataset MVSA.

关键词： Sentiment analysis | Cross-model | Attention mechanism | Semantic association

摘要：Multimodal Sentiment* Analysis (MSA) leverages* | multimodal signals to detect the sentiment* of a video clip* | Sentiment Information Representations (SIR). Additionally | . Despite the impressive performance of previous MSA | approaches, the issue of inherent multimodal representation

关键词： Contrastive learning | Knowledge distilling | Multimodal sentiment analysis

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：Sentiment analysis is crucial in extracting | refine sentiment analysis algorithms, but there is a | framework for personalized sentiment analysis that | performing sentiment analysis. In particular, such | valuable insights from vast amounts of textual data

关键词： Sentiment analysis | Personalization | Persona | Personality | AI | NLP

摘要： sentiment analysis. Although the data types are different | a method named multimodal sentiment analysis based | , there are information expressing the same sentiment | , using sentiment information as a guide to extract text | and image features related to sentiment. Finally

关键词： Multimodal sentiment analysis | Multimodal interaction | Adaptive | Attention mechanism

摘要： become essential to discern the sentiment of such | media users. The paper focuses on the sentiment of | ., automatically assigning sentiment labels based on different | identifying sentiment. Our results show that multimodal | The usage of memes and other visual material

关键词： Multimodal sentiment analysis | Emotion recognition | Meme dataset

摘要：Multimodal Sentiment Analysis (MSA) aims to | Multimodal Counterfactual Inference Sentiment (MCIS | ) analysis framework based on causality rather than | understand human intentions by integrating emotion-related | clues from diverse modalities, such as visual

关键词： Sentiment analysis | Multimodal learning

摘要：The task of dialogue sentiment analysis aims | propose a dialogue sentiment analysis framework that | to identify the sentiment polarity of utterances in | , and sentiment shift detection. These tasks are | logical relationships and sentiment interactions. By

关键词： Dialogue structure | Sentiment analysis | Pre-training model

摘要： sentiment analysis methods that suffer from insufficient | multimodal image sentiment analysis method that integrates | -the-art multimodal image sentiment analysis | features, insufficient analysis of semantic relationship | accuracy of sentiment classification. The experimental

关键词： Image sentiment analysis | text sentiment analysis | RoBERTa model | transformer | decision fusion

摘要： terrible pandemic that the WHO has declared. Sentiment | analysis is a vital technique for figuring out how people | embeddings, the research suggests a novel sentiment | analysis model for COVID-19 tweets using CT-BERT as a | -measure for positive and negative sentiment

关键词： Sentiment analysis | COVID-19 | BERT model

摘要：Sentiment analysis is gaining prominence in | the VADER sentiment analysis engine, to analyze | Italy. Sentiment polarity was extracted from each | the evaluation of patient satisfaction within | healthcare environments. The present article takes

关键词： Text mining | Sentiment analysis | VADER | VADER-IT

摘要：In today's era, Cross-modal Sentiment Analysis | sentiment analysis network (TDiA), which utilizes cross | uni-modal features for sentiment analysis. In TDiA | the publicly available cross-fmodal sentiment | analysis dataset MVSA.

关键词： Sentiment analysis | Cross-model | Attention mechanism | Semantic association

摘要：Multimodal Sentiment Analysis (MSA) leverages | multimodal signals to detect the sentiment of a video clip | Sentiment Information Representations (SIR). Additionally | . Despite the impressive performance of previous MSA | approaches, the issue of inherent multimodal representation

关键词： Contrastive learning | Knowledge distilling | Multimodal sentiment analysis

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：Sentiment analysis is crucial in extracting | refine sentiment* analysis algorithms, but there is a* | framework for personalized sentiment* analysis that* | performing sentiment* analysis. In particular, such* | valuable insights from vast amounts of textual data

摘要： sentiment analysis. Although the data types are different | a method named multimodal sentiment analysis* based* | , there are information expressing the same sentiment | , using sentiment* information as a guide to extract text* | and image features related to sentiment. Finally

摘要： become essential to discern the sentiment* of such* | media users. The paper focuses on the sentiment* of* | ., automatically assigning sentiment* labels based on different* | identifying sentiment. Our results show that multimodal | The usage of memes and other visual material

摘要：Multimodal Sentiment* Analysis (MSA) aims to* | Multimodal Counterfactual Inference Sentiment* (MCIS* | ) analysis* framework based on causality rather than* | understand human intentions by integrating emotion-related | clues from diverse modalities, such as visual

摘要：The task of dialogue sentiment* analysis aims* | propose a dialogue sentiment* analysis framework that* | to identify the sentiment* polarity of utterances in* | , and sentiment* shift detection. These tasks are* | logical relationships and sentiment* interactions. By*

摘要： sentiment analysis methods that suffer from insufficient | multimodal image sentiment* analysis method that integrates* | -the-art multimodal image sentiment analysis | features, insufficient analysis* of semantic relationship* | accuracy of sentiment* classification. The experimental*

摘要：Sentiment analysis is gaining prominence in | the VADER sentiment* analysis engine, to analyze* | Italy. Sentiment* polarity was extracted from each* | the evaluation of patient satisfaction within | healthcare environments. The present article takes

摘要：In today's era, Cross-modal Sentiment Analysis | sentiment analysis network (TDiA), which utilizes cross | uni-modal features for sentiment* analysis. In TDiA* | the publicly available cross-fmodal sentiment | analysis dataset MVSA.

摘要：Multimodal Sentiment* Analysis (MSA) leverages* | multimodal signals to detect the sentiment* of a video clip* | Sentiment Information Representations (SIR). Additionally | . Despite the impressive performance of previous MSA | approaches, the issue of inherent multimodal representation