Data Mining and Big Data [[electronic resource] ] : 8th International Conference, DMBD 2023, Sanya, China, December 9–12, 2023, Proceedings, Part II / / edited by Ying Tan, Yuhui Shi

• Autore: Tan Ying
• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (289 pages)
• Disciplina: 005.3
• Soggetto topico: Application software; Artificial intelligence; Image processing - Digital techniques; Computer vision; Computer and Information Systems Applications; Artificial Intelligence; Computer Imaging, Vision, Pattern Recognition and Graphics
• Altri autori: ShiYuhui
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Information Security Approaches -- A Local Interpretability Model-Based Approach for Black-Box Adversarial Attack -- 1 Introduction -- 2 Related Work -- 2.1 Adversarial Attack Approaches -- 2.2 Interpretability-Based Adversarial Attack Approaches -- 3 Local Interpretability Model-Based Attack Approach -- 3.1 Identify Discriminative Regions by LIME -- 3.2 Black-Box Attack Approaches Based on Discriminative Regions -- 4 Experimental Results -- 4.1 Target Models and Datasets -- 4.2 Comparison Methods -- 4.3 Experimental Results -- 4.4 Sensitivity Analysis of Parameters -- 5 Conclusions -- References -- FirewaLLM: A Portable Data Protection and Recovery Framework for LLM Services -- 1 Introduction -- 1.1 Our Contributions -- 2 Related Work -- 2.1 Large Language Models -- 2.2 LLM Privacy Protection -- 2.3 LSTM -- 2.4 TF-IDF -- 2.5 BERT -- 2.6 AI Model Evaluation -- 3 FirewaLLM Framework -- 3.1 Sensitive Text Discrimination Algorithm -- 3.2 Desensitization Algorithm -- 3.3 Text Recovery Algorithm -- 4 Model Effect Evaluation -- 4.1 Measure Index -- 4.2 Test Datasets -- 4.3 Result -- 4.4 Conclusion -- References -- Data Query and Image Clustering -- AL-SQUARES: SQL Synthesis System with the Addition of Reducer -- 1 Introduction -- 2 Relates Work -- 2.1 Domain Specific Language and Attributes -- 2.2 SQUARES -- 3 Program Synthesis Model Architecture -- 3.1 Problem Formulation -- 3.2 Model Architecture -- 3.3 Neural Network Architecture of the Reducer -- 3.4 LSTM -- 3.5 Attention -- 4 Experiments -- 4.1 Preparation -- 4.2 The Parameter N -- 4.3 Speedup Results -- 5 Discussion -- References -- Query Reverse Engineering of Pre-deleted Uncorrelated Operators -- 1 Introduction -- 2 Background Knowledge -- 2.1 Query Reverse Engineering -- 2.2 Domain-Specific Languages. ; 2.3 Enumeration-Based Program Synthesis -- 3 PdQRE -- 3.1 Structure of PdQRE -- 3.2 Encoding of Data -- 3.3 Structure of Predictor -- 3.4 Generation of Dataset -- 3.5 Training of Predictor -- 4 Experiments and Comparisons -- 4.1 Selection of Hyperparameter -- 4.2 Comparison of PdQRE and SQUARES -- 4.3 Comparison of PdQRE with Other Models -- 5 Conclusions -- References -- No-Reference Quality Assessment for HDR Images Based on Multi-scale Retinex Decomposition -- 1 Introduction -- 2 Proposed Method -- 2.1 Retinex Decomposition -- 2.2 Feature Extraction from Reflectance Maps -- 2.3 Feature Extraction from Luminance Component -- 2.4 Learning Metric -- 3 Experimental Results -- 3.1 Databases -- 3.2 Assessment Criteria -- 3.3 Performance Comparison -- 3.4 Computational Complexity -- 4 Conclusion -- References -- Node Importance-Based Semi-supervised Nonnegative Matrix Factorization for Image Clustering -- 1 Introduction -- 2 Related Works -- 2.1 Unsupervised NMF and Its Variants -- 2.2 Semi-supervised NMF -- 3 The Proposed NISNMF Algorithm -- 3.1 Construction of NISNMF Model -- 3.2 Optimization -- 3.3 Convergence -- 4 Experiments -- 4.1 Experimental Setting -- 4.2 Clustering Comparision -- 4.3 Parameter Sensitivity Analysis -- 5 Conclusion -- References -- An Empirical Study on the Impact of Environmental Policies on Green Total Factor Productivity of Manufacturing Industry in China -- 1 Introduction -- 2 Industry Classification and Green Total Factor Productivity Measurement -- 2.1 Industry Classification -- 2.2 Green Total Factor Productivity Measurement. -- 3 Empirical Analysis -- 3.1 Model Construction -- 3.2 Index Selection and Data Declaration -- 3.3 Empirical Results Analysis -- 4 Conclusion -- References -- Digital Simulation Methods -- Construction of Digital Twin Battlefield with Command and Control as the Core -- 1 Introduction. ; 2 Digital Twin Battlefield Status -- 3 Command and Control System Digital Twin -- 3.1 Modeling Characteristics -- 3.2 Important Role -- 4 Operation Architecture -- 5 Key Technologies -- 5.1 Command and Control System Digital Twin Modeling Technology -- 5.2 Command Elements Drive Digital Twin Battlefield Operation Technology -- 5.3 Command and Control System Digital Twin Virtual-Reality Connection and Interaction Technology -- 6 Application -- 6.1 Assisted Decision-Making Support -- 6.2 SoS Optimization Design -- 7 Conclusion -- References -- A Joint Method for Combat Intent Recognition and Key Information Extraction -- 1 Introduction -- 2 Related Works -- 2.1 Operational Intent Recognition -- 2.2 Combat Information Extraction -- 3 Methods -- 3.1 Combat Intent Recognition -- 3.2 Key Information Extraction -- 3.3 Joint Extraction Method -- 3.4 Concrete Methods -- 4 Experiments -- 4.1 Dataset -- 4.2 Experimental Environment -- 4.3 Experimental Results -- 5 Conclusion -- References -- Theory-Assisted Deep Learning Weapon System Combat Effectiveness Prediction -- 1 Introduction -- 2 Theory-Assisted Model Training -- 2.1 Basic Model Description -- 2.2 Theory-Driven and Data-Driven Hybrid -- 3 Model Based on GA-CNN-LSTM -- 4 Empirical Study -- 4.1 Theoretical Modeling -- 4.2 Data Set Construction -- 4.3 Experimental Environment and Model Building -- 5 Result and Discussion -- 6 Conclusions -- References -- Aerial Scene Understanding Based on Synthetic Data -- 1 Introduction -- 2 Related Work -- 3 Synthetic Drone Raw Data Generation Framework and SynthDrone Dataset -- 3.1 Raw Data Generation -- 3.2 Dataset Post Processing and Statistical Analysis -- 4 Depth Aware Target Distribution Estimation Network -- 5 Experimental Results -- 5.1 Evaluation Metrics -- 5.2 Experiment Results on the SynthDrone Dataset -- 5.3 Cross Domain Density Estimation. ; 5.4 Target Localization and Tracking -- 6 Conclusion -- References -- A New Approach for Ontology Generation from Relational Data Design Patterns -- 1 Introduction -- 2 Background: Ontology Automation -- 3 Ontology Generation from Relational Databases -- 3.1 A Basic Ontology Generator -- 3.2 The JC3IEDM Data -- 3.3 Ontology Generation from Relational DDPs -- 4 Experiments -- 4.1 Comparing Against the Baselines -- 4.2 A Graphical View of the Generated Ontology -- 5 Discussion and Future Work -- 6 Conclusion -- References -- Mining Maximal High Utility Co-location Patterns from Large-Scale Spatial Data -- 1 Introduction -- 2 High Utility Co-location Patterns and Their Maximal Representation -- 3 The Clique-Hash Table-Based Top-Down Traversal Mining Method -- 3.1 Maximal Clique Enumeration -- 3.2 The Hash Table Structure -- 3.3 Top-Down Traversal Mining Maximal HUCPs -- 4 Experimental Study -- 4.1 Experimental Environment -- 4.2 The Effectiveness of Maximal HUCPs -- 4.3 The Efficiency of the Proposed Algorithm -- 5 Conclusion -- References -- Research on the Meta Synthesis Model of Strategic Risk Management for the Complex Weapon Equipment Systems Development -- 1 Introduction -- 2 Concept and Process of Strategic Risk Management for the Complex Weapon Equipment Systems Development -- 3 A Three-Dimensional System Structure for Strategic Risk Management in the Complex Weapon Equipment Systems Development -- 3.1 Time Dimension -- 3.2 Logical Dimension -- 3.3 Knowledge Dimension -- 4 A Meta Synthesis Model for Strategic Risk Management in the Complex Weapon Equipment Systems Development -- 5 An Example of Strategic Risk Integrated Management for a Certain Type of Complex Weapon Equipment Systems Development -- 5.1 Strategic Risk Characteristics of a Certain Type of Complex Weapon Equipment Systems Development. ; 5.2 Comprehensive Risk Management Model for a Certain Type of Complex Weapon Equipment System Development -- 5.3 Use of a Comprehensive Risk Integration Model for the Construction and Development of a Certain Type of Complex Weapon Equipment System -- 6 Epilogue -- References -- A Service-Oriented Data Sharing and Exchange Model -- 1 Introduction -- 2 Related Work -- 2.1 Digital Government -- 2.2 Data Sharing -- 3 Model -- 3.1 Overall Architecture -- 3.2 Business Collaboration Layer -- 3.3 Shared Exchange Layer -- 3.4 Service Access Layer -- 4 Process -- 4.1 Creating Services -- 4.2 Use of Services -- 5 Conclusion -- References -- Integrated Organization and Sharing Method and Platform for AI Computing Resources Based on Digital Object -- 1 Introduction -- 2 Organization of AI Computing Resources Based on Digital Object -- 2.1 Key Technology -- 2.2 AI Computing Resource Digital Object Encapsulation Implementation -- 3 AI Computing Platform Based on Digital Object -- 3.1 Design of AI Computing Platform -- 3.2 Key Capabilities -- 4 Operation Mode and Usage Scenarios -- 4.1 Operation Mode -- 4.2 Application Scenarios -- 5 Conclusion -- References -- Machine Learning for Medical Applications -- Review of Machine Learning Algorithms for Breast Cancer Diagnosis -- 1 Introduction -- 2 Literature Review -- 3 Breast Cancer Dataset -- 4 Breast Cancer Classification Framework -- 4.1 Data Pre-processing -- 4.2 The Breast Cancer Classifiers -- 5 Experimental Study -- 6 Conclusions -- References -- Integrated Patient Care Optimization Model: A Novel Model to Enhancing Medical Alliance Efficiency -- 1 Introduction -- 2 Literature Review -- 3 Model Construction -- 3.1 The Integrated Patient Care Optimization Model -- 3.2 The IPCOM Validation: Simulation -- 4 Results -- 4.1 Parameter Settings -- 4.2 Analysis of Results -- 5 Conclusions -- References. ; A Two-Stage Approach to Optimize Medical Waste Transportation Problem During Pandemic.
• Sommario/riassunto: This two-volume set, CCIS 2017 and 2018 constitutes the 8th International Conference, on Data Mining and Big Data, DMBD 2023, held in Sanya, China, in December 2023. The 38 full papers presented in this two-volume set included in this book were carefully reviewed and selected from 79 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.
• Titolo autorizzato: Data Mining and Big Data
• ISBN: 981-9708-44-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910841859403321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 2018