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BFG: privacy protection framework for internet of medical things based on blockchain and federated learning BFG:基于区块链和联邦学习的医疗物联网隐私保护框架
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-25 DOI: 10.1080/09540091.2023.2199951
Wenkang Liu, Yuxuan He, Xiaoliang Wang, Ziming Duan, Wei Liang, Yuzhen Liu
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引用次数: 1
Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm 基于改进Harris Hawk优化算法的混合入侵检测研究
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-19 DOI: 10.1080/09540091.2023.2195595
Pengzhen Zhou, Huifu Zhang, Wei Liang
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引用次数: 1
Hybrid feature learning framework for the classification of encrypted network traffic 用于加密网络流量分类的混合特征学习框架
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-13 DOI: 10.1080/09540091.2023.2197172
S. Ramraj, G. Usha
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引用次数: 0
Quality medical data management within an open AI architecture - cancer patients case 开放AI架构下的高质量医疗数据管理——癌症患者案例
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-13 DOI: 10.1080/09540091.2023.2194581
Mirjana Ivanovic, Serge Autexier, Miltiadis Kokkonidis, Johannes Rust
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引用次数: 1
Ontology-based semantic data interestingness using BERT models 利用BERT模型实现基于本体的语义数据兴趣
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-11 DOI: 10.1080/09540091.2023.2190499
Abhilash C. Basavaraju, K. Mahesh, Nihar Sanda
The COVID-19 pandemic has generated massive data in the healthcare sector in recent years, encouraging researchers and scientists to uncover the underlying facts. Mining interesting patterns in the large COVID-19 corpora is very important and useful for the decision makers. This paper presents a novel approach for uncovering interesting insights in large datasets using ontologies and BERT models. The research proposes a framework for extracting semantically rich facts from data by incorporating domain knowledge into the data mining process through the use of ontologies. An improved Apriori algorithm is employed for mining semantic association rules, while the interestingness of the rules is evaluated using BERT models for semantic richness. The results of the proposed framework are compared with state-of-the-art methods and evaluated using a combination of domain expert evaluation and statistical significance testing. The study offers a promising solution for finding meaningful relationships and facts in large datasets, particularly in the healthcare sector. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
近年来，COVID-19大流行在医疗保健领域产生了大量数据，鼓励研究人员和科学家揭示潜在的事实。在大型COVID-19语料库中挖掘有趣的模式对决策者来说非常重要和有用。本文提出了一种利用本体和BERT模型在大型数据集中发现有趣见解的新方法。该研究提出了一个框架，通过使用本体将领域知识纳入数据挖掘过程，从数据中提取语义丰富的事实。采用改进的Apriori算法挖掘语义关联规则，并利用BERT模型评估规则的兴趣度。将提出的框架的结果与最先进的方法进行比较，并使用领域专家评估和统计显著性检验相结合的方法进行评估。该研究为在大型数据集中寻找有意义的关系和事实提供了一个有希望的解决方案，特别是在医疗保健部门。©2023作者。由Informa UK Limited出版，以Taylor & Francis Group的名义进行交易。
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引用次数: 1
Discovery of process variants based on trace context tree 基于跟踪上下文树的过程变体发现
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-11 DOI: 10.1080/09540091.2023.2194578
Huan Fang, Wangcheng Liu, Wusong Wang, Shunxiang Zhang
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引用次数: 3
MS_HGNN: a hybrid online fraud detection model to alleviate graph-based data imbalance MS_HGNN:一种缓解基于图的数据不平衡的混合在线欺诈检测模型
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-06 DOI: 10.1080/09540091.2023.2191893
Jing Long, Fei Fang, Cuiting Luo, Y. Wei, T. Weng
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引用次数: 0
FedG2L: a privacy-preserving federated learning scheme base on "G2L" against poisoning attack FedG2L:一种基于“G2L”抗中毒攻击的隐私保护联邦学习方案
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-06 DOI: 10.1080/09540091.2023.2197173
Mengfan Xu, Xinghua Li
{"title":"FedG2L: a privacy-preserving federated learning scheme base on \"G2L\" against poisoning attack","authors":"Mengfan Xu, Xinghua Li","doi":"10.1080/09540091.2023.2197173","DOIUrl":"https://doi.org/10.1080/09540091.2023.2197173","url":null,"abstract":"","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":"53 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91144368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analyzing execution path non-determinism of the Linux kernel in different scenarios 分析不同场景下Linux内核执行路径的不确定性
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-03 DOI: 10.1080/09540091.2023.2192442
Yucong Chen, Xianzhi Tang, Shuaixin Xu, Fangfang Zhu, Qingguo Zhou, T. Weng
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引用次数: 0
Active learning for deep object detection by fully exploiting unlabeled data 通过充分利用未标记数据进行深度目标检测的主动学习
IF 5.3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Connection Science
Pub Date : 2023-04-03 DOI: 10.1080/09540091.2023.2195596
Feixiang Tan, Guansheng Zheng
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引用次数: 0
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