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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1353 条记录，以下是151-160 订阅

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Robust Graph Embedding Recommendation Against data Poisoning Attack

Robust Graph Embedding Recommendation Against Data Poisoning...

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international conference on big data intelligence and computing, datacom 2022

作者： Zhong, Junyan Liu, Chang Wang, Huibin Tian, Lele Zhu, Han Lam, Chan-Tong HSBC Software Development Guangdong Ltd. Guangzhou China Faculty of Humanities and Social Science Macao Polytechnic University China ABB Global Open Innovation Center Shenzhen China Gree Electric Appliances Inc. of Zhuhai Zhuhai China Faculty of Applied Sciences Macao Polytechnic Uniuversity China

ISBN: (纸本)9789819922321

With the development of recommendation system technology, more and more Internet services are applied to recommendation systems. In recommendation systems, matrix factoring is the most widely used technique. However, matrix factoring algorithms are very susceptible to shilling attacks (trust or espionage). The former defends methods against data poisoning attacks focused on detecting individual attack behaviors. But there are few detection methods for group data poisoning attacks. Therefore, we propose a detection method based on Graph Neural Network (GNN) and adversarial learning. We train user-item nodes and edges through a semi-supervised learning approach, improving the robustness of the GNN recommendation system. Our work can be divided into the following parts: Firstly, we review the former recommendation systems and the graph representation learning recommendation systems. Secondly, we analyze the main vulnerabilities of the graph representation learning recommendation systems. Furthermore, the detection methods of data poisoning attacks are analyzed, and the difference between individual data poisoning attacks and group data poisoning attacks are discussed. Finally, we propose a per-process Robust-GNN semi-supervised detection model to conduct group detection on different types of attacks. In addition, we also analyze the sensitivity of the proposed methods. From the experiments results, it can be concluded that we should apply the attention mechanism to the proposed methods which makes it more generalized. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graph neural networks

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Research on Quality Prediction of Optical Modules in 5G Networks 19

Research on Quality Prediction of Optical Modules in 5G Netw...

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2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Li, Bei Liu, Hongjia Liu, Guanghai Sun, Wen Xu, Lexi Xiao, Tian Li, Yi Zhu, Xiaomeng Zheng, Yuting Chen, Qiang Research Institute China United Network Communication Corporation Beijing100048 China Zhejiang Branch of China Unicom Hangzhou310051 China Northwestern Polytechnical University School of Cybersecurity Xi'an710072 China Zte Corporation Hangzhou310012 China

ISBN: (纸本)9798350346558

With the construction of 5G becoming more and more prosperous, the construction and maintenance costs of communication operators are increasing, and the demand for cost reduction and efficiency increase is increasing. Operators expect to improve maintenance efficiency and realize active operation and maintenance. With the help of big data analysis, AI algorithms and digital twin technology, etc., Real-time predictive maintenance alarms can be realized. This article focuses on the evaluation and prediction of optical modules, identifies the health value status more accurately, understands the health value status of optical modules in advance, and maintains and eliminates the hidden dangers for problematic optical modules in advance. © 2022 IEEE.

关键词： big data

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Granular-Ball Three-Way Decision

Granular-Ball Three-Way Decision

引用

international Joint conference on Rough Sets (IJCRS)

作者： Yang, Xin Li, Yanhua Xia, Shuyin Lian, Xiaoyu Wang, Guoyin Li, Tianrui SouthWestern Univ Finance & Econ Sch Comp & Artificial Intelligence Chengdu 611130 Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Computat Intelligence Key Lab Big Data Intelligent Comp Key Lab Cyberspace Big Data Intelligent SecurMin Chongqing 400065 Peoples R China Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Peoples R China

ISBN: (纸本)9783031509582;9783031509599

By thinking, information processing and decision-making in threes, the idea, theory and methods of three-way decision have been successfully applied to various domains. However, the current three-way decision has two following limitations. On the one hand, the narrow three-way decision associated with rough sets either has trouble processing continuous data or fails to represent knowledge by equivalence classes. On the other hand, the inputs of generalized three-way decision are individual objects rather than equivalence classes, which reduces the decision efficiency. To this end, we try to integrate efficient granular-ball computing into three-way decision. Firstly, we propose a novel model, i.e., granular-ball three-way decision to improve the efficiency and robustness of three-way decision. Secondly, sequential three-way decision based on granular-ball is presented to investigate the appropriate multi-granularity structures and represent the same object at different granularities. Finally, we analyze the advantages of granular-balls to strengthen the real-world applications of three-way decision.

关键词： Three-way Decision Sequential Three-way Decision Granular-ball computing Multi-granularity Robustness

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AN EFFECTIVE HYBRID data ANALYTICS TECHNIQUE FOR A 360-DEGREE VIEW OF CUSTOMER data 16

AN EFFECTIVE HYBRID DATA ANALYTICS TECHNIQUE FOR A 360-DEGRE...

引用

16th international conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th international conference on Connected Smart Cities, CSC 2022, 7th international conference on big data Analytics, data Mining and Computational intelligence, bigDaCI 2022, and 11th international conference on Theory and Practice in Modern computing, TPMC 2022 - Held at the 16th Multi conference on Computer Science and Information Systems, MCCSIS 2022

作者： Al Nefaie, Majdah Muthaly, Siva Muthaly, Siva Riyadh Saudi Arabia Head School of Business Melbourne Institute of Technology Australia College of Business and Law RMIT Australia

ISBN: (纸本)9789898704429

Digital transformation has increased the importance of big data analytics. The growth of customer data generated through multiple sources, such as physical stores, online stores and services, social media platforms and multimedia applications, has created complexity in understanding customer behaviours and other related business patterns, such as sales and revenue growth. This means that organisations need a 360-degree view of their customer data from multiple sources to create customer journey recommendation systems and gain business, sales and revenue insights. big and quantitative data, such as data collected from face-to-face surveys from customers in physical stores, have played a critical role in organisational decision making. However, big data requires precise analytical methods and techniques to ensure its credibility and the efficiency of its outputs to the related business. This research paper presents a hybrid big data analytics technique that uses multiple sources of big data from online services and quantitative data collected from face-to-face physical semi-government customer service centres. The study model has been implemented in mega projects such as COVID vaccine centres for semi-government organisations in Saudi Arabian. The output of the study is presented a 360-degree customer view for top management and business developers that helps provide a reliable view of and access to the customer information that businesses and organisations need, such as information on the customer journey combined with sales and revenue forecasts. © MCCSIS *** rights reserved.

关键词： data Analytics

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Research on the intelligent application scenarios of big data technology in customs declaration and clearance

Research on the intelligent application scenarios of big dat...

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2022 international conference on Cloud computing, big data and Internet of Things, 3CBIT 2022

作者： Chen, Xiaoying Guangzhou City University of Technology Guangzhou China

ISBN: (纸本)9781665492256

The 21st century belongs to the century of the Internet, the frequency of big data exchange is becoming more and more frequent, and all walks of life are actively strengthening the research and use of big data technology. A country's customs has the important mission of guarding the security of the country and promoting foreign trade, so it is very important to effectively and safely use big data in customs clearance and customs clearance while realizing the intelligence of the regulatory process. This paper analysis the value and characteristics of big data in the application of international trade customs clearance. At the same time, an operation example of "investigating and handling false exports"is used to show the intelligent supervision scenario of big data customs clearance. Take Nansha Customs and Guangzhou Customs as examples to show the intelligent application of big data in customs. Finally, the future development trend and prospect of big data in customs clearance are further prospected. © 2022 IEEE.

关键词： big data

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Design of Xinjiang Disaster Early Warning Cloud Platform Based on big data Technology 2

Design of Xinjiang Disaster Early Warning Cloud Platform Bas...

引用

2022 2nd international conference on Artificial intelligence, big data and Algorithms, CAIBDA 2022

作者： Zhang, Yunfei Guo, Junjie Wang, Bin Xu, Linlin Urumqi Natural Resources Comprehensive Survey Center China Geological Survey Urumqi830057 China Development Research Center China Geological Survey Beijing100031 China Corps Eleventh Division Second Middle School China

ISBN: (纸本)9783800760268

[Objective] Multiple regional geological disasters are an important factor threatening people's lives and properties. big data disaster warning and disaster relief programs are of great significance. [Results] Aiming at the characteristics of Xinjiang's special landform and environment, a modular disaster disposal scheme based on cloud computing was designed, including a three-level cascade platform of data source module, intranet computing module and extranet application module. Collecting real-time environmental data, the platform processes a large amount of data in parallel through algorithms such as big data and risk assessment. [Conclusion] The processing speed of disaster emergency early warning is improved and the high availability of the platform is enhanced. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： big data

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7th international conference on big data and Cloud computing Challenges, ICBCC 2022

7th International Conference on Big Data and Cloud Computing...

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7th international conference on big data and Cloud computing Challenges, ICBCC 2022

ISBN: (纸本)9789819910502

The proceedings contain 24 papers. The special focus in this conference is on big data and Cloud computing Challenges. The topics include: Early Planning of Virtual Machines to Servers in Cloud Server Farms is an Approach for Energy-Efficient Resource Allocation;performance Analysis of Distributed Algorithms for big data Classification;achieving Sustainability by Rectifying Challenges in IoT-Based Smart Cities;framework for Implementation of Smart Driver Assistance System Using Augmented Reality;ioT-Based Mental Health Monitoring System Using Machine Learning Stress Prediction Algorithm in Real-Time Application;fish Feeder System Using Internet of Things;an Efficient and Recoverable Symmetric data Aggregation Approach for Ensuring the Content Privacy of Internet of Things;Implementation and Comparative Analysis of Various Energy-Efficient Clustering Schemes in AODV;secure Web Gateway on Website in Cloud;adaptive End-To-End Network Slicing on 5G Networks;zero Trust Framework in Integrated Cloud Edge IoT Environment;o2Q: Deteriorating Inventory Model with Stock-Dependent Demand Under Trade Credit Policy;embedding (K9-C9)n into Certain Necklace Graphs;Lyrics Generation Using LSTM and RNN;design a Quantum Cryptography Algorithm and Evaluate the Risks of Quantum-Based Nano computing;human Odor Security Using E-nose;automated Road Surveillance System Using Machine Learning;an Artificial intelligence-Based Technique to Optimize Hybrid Vehicle Using Renewable Energy Sources;stock Market Prediction Using Machine Learning Techniques: A Comparative Study;comparative Study on Different Intrusion Detection datasets Using Machine Learning and Deep Learning Algorithms;mitigating Postnatal Depression: A big data Self-help Therapy.

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Construction of Intelligent Emergency Response Technology System Based on big data Technology

Construction of Intelligent Emergency Response Technology Sy...

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2022 international conference on big data, Information and Computer Network, BDICN 2022

作者： Shi, Huan Hui, Bo Hu, Biao Gu, RongJie The Third Research Institute of Ministry of Public Security Special Technology Division Shanghai China The People's Government of Bayingolian Autonomous Prefecture Koria Science and Technology Informatization Detachment China

ISBN: (纸本)9781665484763

This paper analyzes the problems existing in the existing emergency management technology system in China from various perspectives, and designs the construction of intelligent emergency system in combination with the development of new generation of Internet of Things, big data, cloud computing and artificial intelligence technology. The overall design is based on scientific and technological innovation to lead the reform of emergency management mechanism and process reengineering to build an intelligent emergency technology system characterized by "holographic monitoring, early warning, intelligent research and accurate disposal". To build an intelligent emergency management system that integrates intelligent monitoring and early warning, intelligent emergency disposal, efficient rehabilitation, improvement of emergency standards, safety and operation and maintenance construction. © 2022 IEEE.

关键词： Artificial intelligence

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Machine Learning and big data Based IDS System Extensive Survey

Machine Learning and Big Data Based IDS System Extensive Sur...

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2022 international conference on Innovation and intelligence for Informatics, computing, and Technologies, 3ICT 2022

作者： Alromaihi, Noora Al-Omary, Alauddin Y. University of Bahrain College of Information Technology Sakhir Bahrain

ISBN: (数字)9781665451932

ISBN: (纸本)9781665451932

Network traffic and logs are monitored by intrusion detection systems (IDS) for abnormal behavior that could indicate a security breach. Traditional IDS techniques require a considerable amount of time when processing big amounts of data. It also complicates the system and diminishes its effectiveness. In addition, the time required to analyze the data renders the system open to attack for an extended period of time before an alarm is generated. IDSs increasingly employ machine learning algorithms to enhance their ability to identify threats in the presence of massive volumes of data. This paper will introduce machine learning and IDS integration for big data. This connection will enhance the IDS system, increase its detection capabilities, and produce more accurate IDS results. A comprehensive survey of IDS that employ machine learning and big data is offered. Comparison is made between several machine learning algorithms used to improve IDS and the feature selection conducted on a specific dataset. © 2022 IEEE.

关键词： big data

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Research on Cross-Border Logistics Smart Operation System Using big data and Cloud computing

Research on Cross-Border Logistics Smart Operation System Us...

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2022 international conference on Education, Network and Information Technology, ICENIT 2022

作者： Dong, Haiying Nanjing Polytechnic Institute Department of Economics and Management Nanjing China

ISBN: (纸本)9781665463072

With the advent of the intelligent age, big data technology is increasingly introduced into logistics engineering. In order to solve the problems of lag and deviation in the application of traditional technology, big data technology is introduced to establish a cross-border logistics operation control system to realize the visualization and intelligence of cross-border logistics control. Finally, the effectiveness of the control system is verified through an example. © 2022 IEEE.

关键词： big data

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