检索结果-南通市图书馆

A survey on deep learning for textual emotion analysis in social networks

Digital Communications and Networks 2022年第5期8卷 745-762页

作者： Sancheng Peng Lihong Cao Yongmei Zhou Zhouhao Ouyang Aimin Yang Xinguang Li Weijia Ji Shui Yu Laboratory of Language Engineering and Computing Guangdong University of Foreign StudiesGuangzhou510006China School of English Education Guangdong University of Foreign StudiesGuangzhou510006China School of Information Science and Technology Guangdong University of Foreign StudiesGuangzhou510006China School of Computing University of LeedsWood-house LaneLeedsWest YorkshireLS29JTUnited Kingdom School of Computer Science and Intelligence Education Lingnan Normal UniversityZhanjiang 524048China BNU-UIC Institute of Artificial Intelligence and Future Networks Beijing Normal University(BNU Zhuhai)Zhuhai519087China School of Computer Science University of Technology SydneySydneyNSW 2007Australia

Textual emotion analysis(TEA)aims to extract and analyze user emotional states in *** Deep Learning(DL)methods have developed rapidly,and they have proven to be successful in many fields such as audio,image,and natural language *** trend has drawn increasing researchers away from traditional machine learning to DL for their scientific *** this paper,we provide an overview of TEA based on DL *** introducing a background for emotion analysis that includes defining emotion,emotion classification methods,and application domains of emotion analysis,we summarize DL technology,and the word/sentence representation learning *** then categorize existing TEA methods based on text structures and linguistic types:text-oriented monolingual methods,text conversations-oriented monolingual methods,text-oriented cross-linguistic methods,and emoji-oriented cross-linguistic *** close by discussing emotion analysis challenges and future research *** hope that our survey will assist readers in understanding the relationship between TEA and DL methods while also improving TEA development.

关键词： Text emotion analysis Deep learning Sentiment analysis Pre-training

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Multimodal Sentiment analysis Based on a Cross-Modal Multihead Attention Mechanism

引用

Computers, Materials & Continua 2024年第1期78卷 1157-1170页

作者： Lujuan Deng Boyi Liu Zuhe Li School of Computer and Communication Engineering Zhengzhou University of Light IndustryZhengzhou450002China

Multimodal sentiment analysis aims to understand people’s emotions and opinions from diverse ***-nating or multiplying various modalities is a traditional multi-modal sentiment analysis fusion *** fusion method does not utilize the correlation information between *** solve this problem,this paper proposes amodel based on amulti-head attention ***,after preprocessing the original ***,the feature representation is converted into a sequence of word vectors and positional encoding is introduced to better understand the semantic and sequential information in the input ***,the input coding sequence is fed into the transformer model for further processing and *** the transformer layer,a cross-modal attention consisting of a pair of multi-head attention modules is employed to reflect the correlation between ***,the processed results are input into the feedforward neural network to obtain the emotional output through the classification *** the above processing flow,the model can capture semantic information and contextual relationships and achieve good results in various natural language processing *** model was tested on the CMU Multimodal Opinion Sentiment and emotion Intensity(CMU-MOSEI)and Multimodal emotionLines Dataset(MELD),achieving an accuracy of 82.04% and F1 parameters reached 80.59% on the former dataset.

关键词： emotion analysis deep learning cross-modal attention mechanism

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

emotionMap:Visual analysis of Video emotional Content on a Map

引用

Journal of Computer Science & Technology 2020年第3期35卷 576-591页

作者： Cui-Xia Ma Jian-Cheng Song Qian Zhu Kevin Maher Ze-Yuan Huang Hong-An Wang State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100190China Academy of Arts and Design Tsinghua UniversityBeijing 100084China

emotion plays a crucial role in gratifying users’needs during their experience of movies and TV series,and may be underutilized as a framework for exploring video content and *** this paper,we present emotionMap,a novel way of presenting emotion for daily users in 2D geography,fusing spatio-temporal information with emotional *** interface is composed of novel visualization elements interconnected to facilitate video content exploration,understanding,and *** allows understanding of the overall emotion at a glance while also giving a rapid understanding of the ***,we develop emotionDisc which is an effective tool for collecting audiences’emotion based on emotion representation *** collect audience and character emotional data,and then integrate the metaphor of a map to visualize video content and emotion in a hierarchical *** combines sketch interaction,providing a natural approach for users’active *** novelty and the effectiveness of emotionMap have been demonstrated by the user study and experts’feedback.

关键词： video visualization emotion analysis visual analysis sketch interaction

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

emotion-Aware Music Driven Movie Montage

引用

Journal of Computer Science & Technology 2023年第3期38卷 540-553页

作者：刘伍琴林敏轩黄海斌马重阳宋玉董未名徐常胜 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 101408China The State Key Laboratory of Multimodal Artificial Intelligence System(MAIS) Institute of AutomationChinese Academy of SciencesBeijing 100190China Kuaishou Technology Beijing 100085China School of Mechanical Engineering University of Science and Technology BeijingBeijing 100083China

In this paper, we present emotion-Aware Music Driven Movie Montage, a novel paradigm for the challenging task of generating movie montages. Specifically, given a movie and a piece of music as the guidance, our method aims to generate a montage out of the movie that is emotionally consistent with the music. Unlike previous work such as video summarization, this task requires not only video content understanding, but also emotion analysis of both the input movie and music. To this end, we propose a two-stage framework, including a learning-based module for the prediction of emotion similarity and an optimization-based module for the selection and composition of candidate movie shots. The core of our method is to align and estimate emotional similarity between music clips and movie shots in a multi-modal latent space via contrastive learning. Subsequently, the montage generation is modeled as a joint optimization of emotion similarity and additional constraints such as scene-level story completeness and shot-level rhythm synchronization. We conduct both qualitative and quantitative evaluations to demonstrate that our method can generate emotionally consistent montages and outperforms alternative baselines.

关键词： movie montage emotion analysis audio-visual modality contrastive learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An affective chatbot with controlled specific emotion expression

引用

Science China(Information Sciences) 2022年第10期65卷 122-139页

作者： Chenglin JIANG Chunhong ZHANG Yang JI Zheng HU Zhiqiang ZHAN Guanghua YANG State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications School of Intelligent Systems Science and Engineering Jinan University

Endowing a chatbot with the capability of specific emotion expression will significantly improve both chatbot’s usability and users’ satisfaction. Recently, many studies on open-domain neural emotional,conversational models(chatbots) have been conducted. However, enabling a chatbot to control what kind of emotion to respond to in conversation explicitly is still under exploration. This paper proposes a novel affective chatbot based on the sequence-to-sequence framework, responding with appropriate emotion like a human. In particular, a new module called single emotion generator is designed in the new chatbot model to address the existing issue of controlling over reacting emotion. It enables the chatbot to select the appropriate emotion for a response when interacting with users. In the decoder, an affective lexiconbased method generates emotion-awareness responses based on the specific emotion controlled by the single emotion generator. The proposed chatbot outperforms mainstream baseline algorithms for both semantic fluency and emotion consistence metrics through experimental evaluation. The experimental results also demonstrate that the new chatbot obtains the ability to control the emotion for response explicitly and responds emotionally with the specific emotion.

关键词： natural language generation emotional chatbot sequence-to-sequence emotion distribution emotion analysis

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

analysis of emotions Using Multimodal Data: A Case Study

引用

Journal of Biosciences and Medicines 2023年第12期11卷 54-68页

作者： Toshiya Akiyama Kyoko Osaka Hirokazu Ito Ryuichi Tanioka Allan Paulo Blaquera Leah Anne Christine Bollos Tetsuya Tanioka Graduate School of Health Sciences Tokushima University Tokushima Japan Department of Psychiatric Nursing Nursing Course of Kochi Medical School Kochi University Kochi Japan Department of Nursing Art and Sciences Tokushima University Tokushima Japan Department of Physical Therapy Hiroshima Cosmopolitan University Hiroshima Japan Department of Nursing Outcomes Management Institute of Biomedical Sciences Tokushima University Tokushima Japan

In this case study, we hypothesized that sympathetic nerve activity would be higher during conversation with PALRO robot, and that conversation would result in an increase in cerebral blood flow near the Broca’s area. The facial expressions of a human subject were recorded, and cerebral blood flow and heart rate variability were measured during interactions with the humanoid robot. These multimodal data were time-synchronized to quantitatively verify the change from the resting baseline by testing facial expression analysis, cerebral blood flow, and heart rate variability. In conclusion, this subject indicated that sympathetic nervous activity was dominant, suggesting that the subject may have enjoyed and been excited while talking to the robot (normalized High Frequency emotion was recognized, the examiner-judged “happy” faces and the MTCNN “happy” results were also generally consistent.

关键词： Humanoid Robots Multimodal Data emotion analysis

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Brief Overview of Intelligent Education

引用

Journal of Contemporary Educational Research 2021年第8期5卷 187-192页

作者： Tiejun Shao Jianshe Zhou Capital Normal University Beijing 100048 China North China Institute of Science and Technology Langfang 065201China Research Center For Language Intelligence of China Beijing 100048China

Intelligent Education uses Al technology as a means in the education ecology to promote the automation and intelligence of education and *** reshapes the education ecology,adding Al things to the traditional education ecology that dominated by teachers and *** IE technology is widely used,there is little discussion about a comprehensive overview of *** goal and connotation of IE is ***,the emotional,ethical,Al technology as well as supervision and management perspectives in IE are discussed *** core goal of IE is putted forward that is human-oriented and individualized development of students ***,the education ecology with dual-teacher collaborative in intelligence education was proposed.

关键词： Artificial intelligence Intelligent education emotion analysis

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

机器学习视域下融合情感元素的社交网络信息交互度量化分析

引用

图书馆学情报学 2021年第11期

作者：马捷郝志远

数字信息时代，社交网络成为用户聚焦热点话题的讨论平台。为正确引导热点话题在社交网络中的舆情走向，减少信息传播过程中产生的负面影响，本文从交互与信息行为的角度出发，以社交网络中用户的真实评论数据作为研究对象，利用机器学... 详细信息

数字信息时代，社交网络成为用户聚焦热点话题的讨论平台。为正确引导热点话题在社交网络中的舆情走向，减少信息传播过程中产生的负面影响，本文从交互与信息行为的角度出发，以社交网络中用户的真实评论数据作为研究对象，利用机器学习中的密度峰值聚类算法确认用户的解读倾向类别。同时，参考已有的情感极性值计算方法，融入方差加权信息熵的基本策略，提出了社交网络信息交互度量化模型，通过计算话题不同解读倾向所映射的信息交互度，厘清了热点话题的受热议程度和舆情的演化趋势。实例研究表明，基于情感分析视角构建的信息交互度计量模型，量化了热点话题的信息价值，对于推动互联网健康文明发展，以及加强相关部门的网络监管能力具有重要的理论意义。

关键词：社交网络网络舆情情感分析信息交互度机器学习 Social network Internet public opinion emotion analysis Information interaction degree Machine learning

来源：人大复印报刊资料评论

在线全文

人大复印报刊资料

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：