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International Journal on Semantic Web and Information Systems最新文献

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A Web Semantic Mining Method for Fake Cybersecurity Threat Intelligence in Open Source Communities 开源社区中虚假网络安全威胁情报的网络语义挖掘方法
International Journal on Semantic Web and Information Systems Pub Date : 2024-08-08 DOI: 10.4018/ijswis.350095
Zhihua Li, Xinye Yu, Yukai Zhao
{"title":"A Web Semantic Mining Method for Fake Cybersecurity Threat Intelligence in Open Source Communities","authors":"Zhihua Li, Xinye Yu, Yukai Zhao","doi":"10.4018/ijswis.350095","DOIUrl":"https://doi.org/10.4018/ijswis.350095","url":null,"abstract":"In order to overcome the challenges of inadequate classification accuracy in existing fake cybersecurity threat intelligence mining methods and the lack of high-quality public datasets for training classification models, we propose a novel approach that significantly advances the field. We improved the attention mechanism and designed a generative adversarial network based on the improved attention mechanism to generate fake cybersecurity threat intelligence. Additionally, we refine text tokenization techniques and design a detection model to detect fake cybersecurity threats intelligence. Using our STIX-CTIs dataset, our method achieves a remarkable accuracy of 96.1%, outperforming current text classification models. Through the utilization of our generated fake cybersecurity threat intelligence, we successfully mimic data poisoning attacks within open-source communities. When paired with our detection model, this research not only improves detection accuracy but also provides a powerful tool for enhancing the security and integrity of open-source ecosystems.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"22 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927144","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 Insights Into the Classification of Folk Paper-Cut Cultural Genes 语义网对民间剪纸文化基因分类的启示
International Journal on Semantic Web and Information Systems Pub Date : 2024-08-08 DOI: 10.4018/ijswis.350266
Xuemiao Chen, Varsha Arya
{"title":"Semantic Web Insights Into the Classification of Folk Paper-Cut Cultural Genes","authors":"Xuemiao Chen, Varsha Arya","doi":"10.4018/ijswis.350266","DOIUrl":"https://doi.org/10.4018/ijswis.350266","url":null,"abstract":"This study aims to classify folk paper-cut patterns by regional culture, leveraging Semantic Web and LSTM technologies to discern how these patterns reflect distinct cultural characteristics. By developing an LSTM model capable of recognizing and categorizing these patterns, our study not only demonstrates high accuracy in classifying regional cultural genes but also reveals the depth of cultural heritage embedded in paper-cut art. The findings underscore the potential of computational methods in understanding and preserving the rich tapestry of cultural expressions through paper cuts. This work sets a foundation for future explorations into the digital preservation of cultural heritage, highlighting the critical role of technology in safeguarding and interpreting traditional arts in the context of regional culture.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926934","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
Differential Feature Fusion, Triplet Global Attention, and Web Semantic for Pedestrian Detection 差异特征融合、三重全局注意力和网络语义用于行人检测
International Journal on Semantic Web and Information Systems Pub Date : 2024-07-16 DOI: 10.4018/ijswis.345651
Sha Tao, Zhenfeng Wang
{"title":"Differential Feature Fusion, Triplet Global Attention, and Web Semantic for Pedestrian Detection","authors":"Sha Tao, Zhenfeng Wang","doi":"10.4018/ijswis.345651","DOIUrl":"https://doi.org/10.4018/ijswis.345651","url":null,"abstract":"In complex environments and crowded pedestrian scenes, the overlap or loss of local features is a pressing issue. However, existing methods often struggle to strike a balance between eliminating interfering features and establishing feature connections. To address this challenge, we introduce a novel pedestrian detection approach called Differential Feature Fusion under Triplet Global Attention (DFFTGA). This method merges feature maps of the same size from different stages to introduce richer feature information. Specifically, we introduce a pixel-level Triplet Global Attention (TGA) module to enhance feature representation and perceptual range. Additionally, we introduce a Differential Feature Fusion (DFF) module, which optimizes features between similar nodes for filtering. This series of operations helps the model focus more on discriminative features, ultimately improving pedestrian detection performance. Compared to benchmarks, we achieve significant improvements and demonstrate outstanding performance on datasets such as CityPersons and CrowdHuman.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"11 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141640700","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 Secure Data E-Governance for Healthcare Application in Cyber Physical Systems 网络物理系统中医疗保健应用的安全数据电子政务
International Journal on Semantic Web and Information Systems Pub Date : 2024-07-16 DOI: 10.4018/ijswis.345934
Geetanjali Rathee, Hemraj Saini, Sahil Garg, Bong Jun Choi, Mohammad Mehedi Hassan
{"title":"A Secure Data E-Governance for Healthcare Application in Cyber Physical Systems","authors":"Geetanjali Rathee, Hemraj Saini, Sahil Garg, Bong Jun Choi, Mohammad Mehedi Hassan","doi":"10.4018/ijswis.345934","DOIUrl":"https://doi.org/10.4018/ijswis.345934","url":null,"abstract":"The bio-medical devices gather patient information and communicate it to data consumers via wireless networks to take the appropriate action and decision by informing the doctors. However, IoMT is adopted by healthcare departments with a greater speed, yet the majority of devices are limited to resource constraints and security perspectives. The classical e-healthcare systems that are centric have the inherent problem of single-point failure with low transparency and low control over records. Many proposals have been validated in IoT for addressing the inadequate computing and storage of records through sensors. The main focus of this paper is to propose a novel hybrid architecture called Zero Trust Blockchain Architecture for decentralized E-health-CPS systems to support low latency along with storage and processing of records while monitoring the patients. In addition, a probability distribution function may further draft an accurate and real-time monitoring of patients. The proposed mechanism is analyzed against adequate decision, storage, accuracy and transmission of records.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"64 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643522","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 Review of Semantic Medical Image Segmentation Based on Different Paradigms 基于不同范式的医学图像语义分割综述
International Journal on Semantic Web and Information Systems Pub Date : 2024-06-06 DOI: 10.4018/ijswis.345246
Jianquan Tan, Wenrui Zhou, Ling Lin, Huxidan Jumahong
{"title":"A Review of Semantic Medical Image Segmentation Based on Different Paradigms","authors":"Jianquan Tan, Wenrui Zhou, Ling Lin, Huxidan Jumahong","doi":"10.4018/ijswis.345246","DOIUrl":"https://doi.org/10.4018/ijswis.345246","url":null,"abstract":"In recent years, with the widespread application of medical images, the rapid and accurate identification of these regions of interest in a large number of medical images has received widespread attention. This article provides a review of medical image segmentation methods based on deep learning. Firstly, an overview of medical image segmentation methods was provided in the relevant knowledge, segmentation types, segmentation processes, and image processing applications. Secondly, the applications of supervised, semi supervised, and unsupervised methods in medical image segmentation were discussed, and their advantages, disadvantages, and applicable scenarios were revealed through the application of a large number of specific segmentation examples in practical scenarios. Finally, the commonly used medical image segmentation datasets and evaluation indicators were introduced, and the current medical image segmentation methods were summarized and prospected. This review provides a comprehensive and in-depth understanding for researchers in the field of medical image segmentation, and provides valuable references for the design and implementation of future related work.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"47 2‐3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376604","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
EPSSNet EPSSNet
International Journal on Semantic Web and Information Systems Pub Date : 2024-04-02 DOI: 10.4018/ijswis.342087
Zechun Cao, German Zavala Villafuerte, Joseph Almaznaai
{"title":"EPSSNet","authors":"Zechun Cao, German Zavala Villafuerte, Joseph Almaznaai","doi":"10.4018/ijswis.342087","DOIUrl":"https://doi.org/10.4018/ijswis.342087","url":null,"abstract":"Fast and accurate segmentation is important for robot judgement, e.g. robot detection, segmentation, and control. Most researchers have focused on deploying lightweight semantic segmentation models into robot services. The problem is that the critical interaction between semantic segmentation and boundaries is ignored. In this chapter, the authors propose a lightweight parallel execution model (EPSSNet) based on semantic flow branch (SFB), edge flow branch (EFB) and self-adapting weighting fusion (SAWF) for mobile robot service projects. The semantic flow branching module is used to obtain accurate object shape features. The boundary constraint module uses multiple convolution and upsampling to distinguish boundary features from semantic features. In order to adaptively fuse boundary features with semantic segmentation features, the SAWF is proposed. It adaptively fuses semantic and boundary features by learning boundary and semantic feature fusion weights. Detailed experimental results on Cityscapes, Pascal VOC 2012 and ADE20k datasets demonstrate the superior performance of our approach.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"135 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140752817","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
Community Detection on Social Networks With Sentimental Interaction 社交网络上的情感互动社区检测
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-27 DOI: 10.4018/ijswis.341232
Bingdao Feng, Fangyu Cheng, Yanfei Liu, Xinglong Chang, Xiaobao Wang, Di Jin
{"title":"Community Detection on Social Networks With Sentimental Interaction","authors":"Bingdao Feng, Fangyu Cheng, Yanfei Liu, Xinglong Chang, Xiaobao Wang, Di Jin","doi":"10.4018/ijswis.341232","DOIUrl":"https://doi.org/10.4018/ijswis.341232","url":null,"abstract":"Many studies on community detection are mainly based on the similarity in friendship between users. Recent studies have started to explore node contents to identify semantically meaningful communities. However, the sentimental interaction information which plays an important role in community detection is often ignored. By analyzing and utilizing the abundant sentimental interaction information, one can not only more precisely identify the communities, but also discover the interesting interactions and conflicts between these communities. Based on this concept, the authors propose a new Community Sentiment Diffusion Detection Model (CSDD), which utilizes sentimental information embedded in forward posts. Furthermore, the authors present an efficient variational algorithm for model inference. The community detection results have been verified on two large Twitter datasets. It is experimentally demonstrated that we can provide a fine-grained view of sentimental interaction between communities and discover the mechanism of sentiment diffusion between communities.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"40 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140376937","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-Rich Recommendation System for Medical Emergency Response System 医疗应急系统的语义丰富推荐系统
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-26 DOI: 10.4018/ijswis.341231
R. Karthika, L. J. Deborah, Wenying Zheng, Fayez Alqahtani, Amr M. Tolba, B. G. Krishnan, Ritika Bansal
{"title":"Semantic-Rich Recommendation System for Medical Emergency Response System","authors":"R. Karthika, L. J. Deborah, Wenying Zheng, Fayez Alqahtani, Amr M. Tolba, B. G. Krishnan, Ritika Bansal","doi":"10.4018/ijswis.341231","DOIUrl":"https://doi.org/10.4018/ijswis.341231","url":null,"abstract":"The emergency response process consists of methodical and coordinated series of actions and protocols executed by individuals and organizations to proficiently address crises. When planning for medical emergencies, it is vital to work with responsive medical organizations to ensure good communication and coordination. Unlike e-government processes, emergency response processes are focused on knowledge and may frequently change as the emergency situation develops. It is important to change the emergency response plan for dynamic situations and the proposed method helps to create a flexible plan for emergency responses. The proposed approach uses a system for organizing knowledge to figure out the needs and the resources essential for an emergency. It helps to identify the organizations to be involved based on their rules for mutual aid and jurisdiction. Experimental analysis shows that the proposed method outperforms Smart-c and DCERP in suggesting a greater number of hospitals during medical emergency and achieves 0.8, 0.9 and 0.9 precision, recall, and f-measure approximately.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"62 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140378147","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 Trusted Authentication Scheme Using Semantic LSTM and Blockchain in IoT Access Control System 物联网访问控制系统中使用语义 LSTM 和区块链的可信身份验证方案
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-26 DOI: 10.4018/ijswis.341233
Ge Zhao, Xiangrong Li, Hao Li
{"title":"A Trusted Authentication Scheme Using Semantic LSTM and Blockchain in IoT Access Control System","authors":"Ge Zhao, Xiangrong Li, Hao Li","doi":"10.4018/ijswis.341233","DOIUrl":"https://doi.org/10.4018/ijswis.341233","url":null,"abstract":"In edge computing scenarios, due to the wide distribution of devices, complex application environments, and limited computing and storage capabilities, their authentication and access control efficiency is low. To address the above issues, a secure trusted authentication scheme based on semantic Long Short-Term Memory (LSTM) and blockchain is proposed for IoT applications. The attribute-based access control model is optimized, combining blockchain technology with access control models, effectively improving the robustness and credibility of access control systems. Semantic LSTM is used to predict environmental attributes that can further restrict user access and dynamically meet the minimum permission granting requirements. Experiments show that when the number of certificates is 60, the computational overhead of the proposed method is only 203s, which is lower than other state-of-the-art methods. Therefore, the performance of the proposed schema in information security protection in IoT environments shows promise as a scalable authentication solution for IoT applications.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"52 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140378487","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-Based Optimization of Deep Learning for Efficient Real-Time Medical Image Segmentation 基于语义的深度学习优化，实现高效的实时医学图像分割
International Journal on Semantic Web and Information Systems Pub Date : 2024-03-20 DOI: 10.4018/ijswis.340938
Zhenkun Wei, Jia Liu, Yu Yao
{"title":"Semantic-Based Optimization of Deep Learning for Efficient Real-Time Medical Image Segmentation","authors":"Zhenkun Wei, Jia Liu, Yu Yao","doi":"10.4018/ijswis.340938","DOIUrl":"https://doi.org/10.4018/ijswis.340938","url":null,"abstract":"In response to the critical need for advanced solutions in medical imaging segmentation, particularly for real-time applications in diagnostics and treatment planning, this study introduces SM-UNet. This novel deep learning architecture efficiently addresses the challenge of real-time, accurate medical image segmentation by integrating convolutional neural network (CNN) with multilayer perceptron (MLP). The architecture uniquely combines an initial convolutional encoder for detailed feature extraction, MLP module for capturing long-range dependencies, and a decoder that merges global features with high-resolution CNN map. Further optimization is achieved through a tokenization approach, significantly reducing computational demands. Its superior performance is confirmed by evaluations on standard datasets, showing interaction times drastically lower than comparable networks—between 1/6 to 1/10, and 1/25 compared to SOTA models. These advancements underscore SM-UNet's potential as a groundbreaking tool for facilitating real-time, precise medical diagnostics and treatment strategies.","PeriodicalId":508238,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140389146","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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