Advanced data mining and applications : 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, November 28-30, 2022, Proceedings, Part II / / Weitong Chen [and five others] editors

• Pubblicazione: Cham, Switzerland : , : Springer, , [2022]; ©2022
• Descrizione fisica: 1 online resource (500 pages)
• Disciplina: 006.31
• Soggetto topico: Data mining
• Persona (resp. second.): ChenWeitong
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Text Mining -- Towards Idea Mining: Problem-Solution Phrase Extraction from Text -- 1 Introduction -- 2 Related Work -- 2.1 Problem Formation -- 3 Methodology -- 3.1 Models for Extracting Problem-Solution Phrases -- 4 Experiment -- 4.1 Dataset UCCL1000 -- 4.2 Dataset NIPS488 -- 4.3 Dataset Summary -- 4.4 Text Preprocessing -- 4.5 Input Representations -- 4.6 Training and Evaluation -- 4.7 Result Analysis -- 5 Discussion -- 6 Future Work -- 7 Conclusion -- References -- Spam Email Categorization with NLP and Using Federated Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Federated Phishing Filter (FPF) -- 3.1 Natural Language Processing -- 3.2 Deep Learning Model for Spam Categorization -- 3.3 Spam Detection and Categorization Model -- 3.4 Federated Learning -- 3.5 Federated Training Models -- 3.6 Federated Averaging (FA) -- 3.7 Federated Averaging Strategies -- 3.8 Equal Weighting (EWS) -- 3.9 Weighted Average (WAS) -- 3.10 Datasets -- 4 Empirical Evaluation -- 4.1 Comparison of EWS and AWS Averaging Strategies -- 4.2 Features Performance Comparison -- 5 Conclusion and Future Work -- References -- SePass: Semantic Password Guessing Using k-nn Similarity Search in Word Embeddings*-12pt -- 1 Introduction -- 2 Related Work -- 3 Semantic Password Guessing -- 3.1 Generation of New Password Candidates -- 3.2 Sorting of the Password Candidates -- 4 Test Bed -- 4.1 Data Sets -- 4.2 Compared Methods -- 4.3 Experimental Set-Up and Evaluation Metric -- 5 Results and Discussion -- 5.1 Accuracy Results -- 5.2 Unseen Base Words -- 6 Conclusion -- References -- DeMRC: Dynamically Enhanced Multi-hop Reading Comprehension Model for Low Data -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Sentence Filtering Model -- 3.2 Answer Prediction Model. ; 3.3 Self-training Augmentation Based on External Data -- 4 Experiments -- 4.1 Data Set -- 4.2 Implementation Details -- 5 Results -- 6 Conclusion -- References -- ESTD: Empathy Style Transformer with Discriminative Mechanism -- 1 Introduction -- 2 Related Work -- 2.1 NLP for Online Mental Health Assistance -- 2.2 Text Style Transfer -- 2.3 Discriminatory Mechanism -- 3 Methodology -- 3.1 Empathic Expression Calculation -- 3.2 ESTD Framework -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Evaluation Metrics -- 4.4 Ablation Study -- 4.5 Results -- 5 Conclusion -- References -- Detection Method of User Behavior Transition on Computer -- 1 Introduction -- 2 Related Work -- 2.1 Image Classification and Clustering -- 2.2 Search and Operation Automation -- 2.3 User Behavior Analytics -- 3 Detection Method of User Behavior Transition -- 3.1 Overview -- 3.2 Feature Extraction -- 3.3 Time-Series Grouping Function -- 3.4 Time-Series Features Grouping Function -- 3.5 User Behavior Transition Detection Function -- 4 Experiment -- 4.1 Our Dataset -- 4.2 Experiment Results -- 4.3 Discussion -- 5 Conclusion -- References -- Image, Multimedia and Time Series Data Mining -- Ensemble Image Super-Resolution CNNs for Small Data and Diverse Compressive Models -- 1 Introduction -- 1.1 Contribution -- 2 Foundational Work and Background -- 2.1 Sparse Representations -- 2.2 Miralon Areal Density Maps -- 3 Proposed Method -- 4 Experimental Results -- 4.1 Training Details -- 4.2 Reconstruction Quality on Testing Images -- 4.3 Application of Miralon Areal Density Maps -- 5 Conclusion -- References -- Optimizing MobileNetV2 Architecture Using Split Input and Layer Replications for 3D Face Recognition Task -- 1 Introduction -- 2 Backgrounds -- 2.1 Related Works -- 2.2 Convolutional Neural Network (CNN) -- 3 Methodology -- 3.1 Data Gathering. ; 3.2 Preprocessing -- 3.3 Model Overview -- 3.4 Metrics -- 3.5 Training Configuration -- 3.6 Automatic Model Finding -- 4 Experimental Results -- 4.1 Comparison Between 2D and 3D Face Recognition Models -- 4.2 Comparison Between RGBD and RGB+D Face Recognition Models -- 4.3 Comparison Between Baseline MobileNetV2 and RGB+D MobileNetV2 with Layer Replication -- 4.4 Comparison Between Our Baseline Model and EffiencientNet on CelebA Dataset -- 5 Conclusion and Future Work -- References -- GANs for Automatic Generation of Data Plots -- 1 Introduction -- 2 Generative Adversarial Networks -- 3 Related Work -- 4 Methodology -- 5 Results -- 6 Conclusion -- References -- An Explainable Approach to Semantic Link Mining in Multi-sourced Dynamic Data -- 1 Introduction -- 2 Related Work -- 2.1 Knowledge Graph Link Prediction -- 2.2 Semantic Data Integration -- 3 Preliminaries -- 4 Our Approach -- 4.1 Our Framework -- 4.2 KG-Based Integration -- 4.3 Rule-Based Link Prediction -- 5 An Application Case -- 6 Evaluation -- 6.1 Static Link Prediction -- 6.2 Dynamic Link Prediction -- 7 Conclusion -- References -- Information Mining from Images of Pipeline Based on Knowledge Representation and Reasoning -- 1 Introduction -- 2 Related Work -- 2.1 Pipeline Defects Identification -- 2.2 Ontology for Knowledge Formalization -- 3 PDI Ontology Construction -- 3.1 Knowledge Resource -- 3.2 Ontology Development for PDI -- 3.3 Reasoning Rules for PDI -- 4 Case Study -- 4.1 Selected Pipeline Images with Common Defect Types -- 4.2 The Attribute Information of Pipeline Images -- 4.3 Mapping Rules for Images Instantiation in PDI Ontology -- 4.4 Knowledge Reasoning -- 4.5 Discussion -- 5 Conclusion -- References -- Binary Gravitational Subspace Search for Outlier Detection in High Dimensional Data Streams -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation. ; 4 Binary Gravitational Subspace Search for Outlier Detection in High Dimensional Data Streams -- 4.1 Subspace Search with Adapted Binary GSA -- 4.2 Solution Overview -- 5 Experimental Study and Results Analysis -- 5.1 Experimentation Setting -- 5.2 Results and Analysis -- 6 Conclusion and Future Works -- References -- Classification, Clustering and Recommendation -- Signal Classification Using Smooth Coefficients of Multiple Wavelets to Achieve High Accuracy from Compressed Representation of Signal -- 1 Introduction -- 2 Wavelets -- 2.1 DWT -- 2.2 MDWT -- 2.3 Energy Distribution -- 3 Proposed Technique -- 3.1 Advantages -- 3.2 Steps in the Proposed Technique: MWCSC -- 4 Experimental Results -- 4.1 Classification Methods Used -- 4.2 Arrowhead Data -- 4.3 Mallat Data -- 4.4 Ford Data -- 5 Conclusion -- References -- On Reducing the Bias of Random Forest -- 1 Introduction -- 2 The Proposed Technique -- 3 Experimental Results -- 4 Conclusion -- References -- A Collaborative Filtering Recommendation Method with Integrated User Profiles*-12pt -- 1 Introduction -- 2 Proposed Method -- 2.1 User Profile Labeling System -- 2.2 User Profile Construction and Similarity Calculation -- 2.3 User Clustering -- 2.4 Collaborative Filtering -- 3 Performance Analysis -- 3.1 Experimental Method -- 3.2 Experimental Result -- 4 Conclusion -- References -- A Quality Metric for K-Means Clustering Based on Centroid Locations -- 1 Introduction -- 2 Related Work -- 3 New Quality Metrics -- 3.1 Reduced 2R Metric -- 3.2 Implicit Assumptions in K-Means Algorithm -- 3.3 Covariant Metric (MC) -- 3.4 Quantifying Index Performance -- 4 Experiments on Synthetic Data -- 4.1 Data Generation -- 4.2 Analysis of Synthetic Data -- 4.3 Results and Discussion -- 5 Experiments on Real Data -- 5.1 Variable Selection -- 5.2 Data Sets -- 6 Comparison with Other Indexes -- 7 Limitations. ; 8 Conclusion -- References -- Clustering Method for Touristic Photographic Spots Recommendation -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 3.1 Global Clustering -- 3.2 Local Clustering -- 3.3 Indexes and Validation -- 3.4 TPS Qualification -- 4 Experiments -- 4.1 Data Processing -- 4.2 Global Clustering Comparison -- 4.3 Local Clustering Comparison -- 4.4 Spot Qualification -- 5 Conclusion and Future Work -- References -- Personalized Federated Learning with Robust Clustering Against Model Poisoning -- 1 Introduction -- 2 Related Work -- 2.1 PFL -- 2.2 Robust Clustering -- 2.3 Model Poisoning and Anomaly Detection -- 3 Methodology -- 3.1 PFL -- 3.2 LOF -- 3.3 Proposed Method -- 4 Algorithm -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Experimental Study -- 6 Conclusion -- References -- A Data-Driven Framework for Driving Style Classification -- 1 Introduction -- 2 State of the Art -- 3 Problem Statement -- 4 Proposed Solution -- 4.1 Dataset Description -- 4.2 Pre-processing -- 4.3 Feature Engineering -- 4.4 Neural Architecture Search -- 5 Results -- 5.1 Selection of Time-Window for Aggregation -- 5.2 Comparison of Different Models -- 6 Conclusion and Future Work -- References -- Density Estimation in High-Dimensional Spaces: A Multivariate Histogram Approach -- 1 Introduction -- 2 Background and Related Work -- 2.1 Basic Concepts -- 2.2 Approaches to Density Estimation -- 2.3 Applications in Research -- 2.4 Example: Density of the Old Faithful Dataset -- 3 A Multivariate Histogram-Based Approach -- 3.1 Define Hypergrid -- 3.2 Calculate Relative Frequencies -- 3.3 Calculate Hypervolumes and Density Estimates -- 3.4 Estimate Density for Datasets with Missing Values -- 4 Evaluation and Results -- 4.1 Computational Performance -- 4.2 Measuring Density with Categorical Variables -- 4.3 Measuring Density with Missing Values. ; 5 Conclusions.
• Titolo autorizzato: Advanced Data Mining and Applications
• ISBN: 3-031-22137-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910632469803321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture notes in computer science. . -Lecture notes in artificial intelligence ; ; 13726.