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Multimodal Sentiment Analysis Method Based on Hierarchical Adaptive Feature Fusion Network 基于层次自适应特征融合网络的多模态情感分析方法
International Journal on Semantic Web and Information Systems Pub Date : 2024-01-12 DOI: 10.4018/ijswis.335918
Huchao Zhang
{"title":"Multimodal Sentiment Analysis Method Based on Hierarchical Adaptive Feature Fusion Network","authors":"Huchao Zhang","doi":"10.4018/ijswis.335918","DOIUrl":"https://doi.org/10.4018/ijswis.335918","url":null,"abstract":"The traditional multi-modal sentiment analysis (MSA) method usually considers the multi-modal characteristics to be equally important and ignores the contribution of different modes to the final MSA result. Therefore, an MSA method based on hierarchical adaptive feature fusion network is proposed. Firstly, RoBERTa, ResViT, and LibROSA are used to extract different modal features and construct a layered adaptive multi-modal fusion network. Then, the multi-modal feature extraction module and cross-modal feature interaction module are combined to realize the interactive fusion of information between modes. Finally, an adaptive gating mechanism is introduced to design a global multi-modal feature interaction module to learn the unique features of different modes. The experimental results on three public data sets show that the proposed method can make full use of multi-modal information, outperform other advanced comparison methods, improve the accuracy and robustness of sentiment analysis, and is expected to achieve better results in the field of sentiment analysis.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":" 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139623925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Network Intrusion Detection Method for Various Information Systems Based on Federated and Deep Learning 基于联盟和深度学习的各种信息系统网络入侵检测方法
International Journal on Semantic Web and Information Systems Pub Date : 2024-01-07 DOI: 10.4018/ijswis.335495
Qi Zhou, Chun Shi
{"title":"A Network Intrusion Detection Method for Various Information Systems Based on Federated and Deep Learning","authors":"Qi Zhou, Chun Shi","doi":"10.4018/ijswis.335495","DOIUrl":"https://doi.org/10.4018/ijswis.335495","url":null,"abstract":"Under the premise of ensuring data privacy, traditional network intrusion detection (NID) methods cannot achieve high accuracy for different types of intrusions. A NID method combining transformer and federated learning (FedL) is proposed for this purpose. First, a multi-party collaborative learning framework was built based on FedL, which achieved data exchange and sharing. Then, by introducing the self-attention mechanism (AttM) to improve the traditional transformer, it could quickly converge. Finally, an NID model integrating transformer and FedL was constructed by combining DNN, GRU, and an encoder module composed of improved transformer, achieving accurate detection of network intrusion. The proposed NID method was compared with the other three methods. The results show that the proposed method has the highest NID accuracy and F1 score on the NSL-KDD and UNSW-NB15 dataset, with the highest accuracy reaching 99.65% and 89.25%, while the F1 score has the highest accuracy, reaching 99.45% and 88.13%, outperforming the other three comparative algorithms in terms of performance.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"33 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Semantic Web-Based Structural Equation Modeling and Mediating Effects Are Used to Investigate Key Factors 利用基于语义网的结构方程模型和中介效应调查关键因素
International Journal on Semantic Web and Information Systems Pub Date : 2024-01-07 DOI: 10.4018/ijswis.335641
Hao Ma, Yi Zhi Gai
{"title":"Semantic Web-Based Structural Equation Modeling and Mediating Effects Are Used to Investigate Key Factors","authors":"Hao Ma, Yi Zhi Gai","doi":"10.4018/ijswis.335641","DOIUrl":"https://doi.org/10.4018/ijswis.335641","url":null,"abstract":"Land desertification is the key contradiction restricting the sustainable development of Chinese society. Farmers and herders' behavior in desert management is particularly important for the smooth development of the desertification control project. Although farmers and herders express willingness, they do not engage in desert management behavior. The research through random sampling survey analyzes survey data from 572 farmers and herders in the Kubuqi Desert region of Inner Mongolia using structural equation modeling and mediation analysis, based on the TPB. The aim is to understand the paradoxical willingness and behavior of farmers and herders to participate in desert management. The study found that farmers and herders' willingness to participate is a crucial factor that influences their behavior. The authors suggest cultivating a sense of ecological responsibility and strengthening ecological education to guide the behavior of farmers and herders towards more sustainable practices.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"22 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139448348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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