Advanced Data Mining and Applications

Name: Advanced Data Mining and Applications | 17th International Conference, ADMA 2021, Sydney, NSW, Australia, February 2-4, 2022, Proceedings, Part II
Brand: Springer
Price: 80.24 EUR
Availability: OnlineOnly

17th International Conference, ADMA 2021, Sydney, NSW, Australia, February 2-4, 2022, Proceedings, Part II

Bohan Li Lin Yue Jing Jiang Weitong Chen Xue Li Guodong Long Fei Fang Han Yu(Herausgeber*in)

Springer (Verlag)

Erschienen am 31. Januar 2022

XVII, 419 Seiten

E-Book

PDF mit Wasserzeichen-DRM

Systemvoraussetzungen

978-3-030-95408-6 (ISBN)

80,24 €inkl. 7% MwSt.

Systemvoraussetzungen

für PDF mit Wasserzeichen-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

Weitere Details

Weitere Ausgaben

Inhalt

Intro
Preface
Organization
Contents - Part II
Contents - Part I
Pattern Mining
SMIM Framework to Generalize High-Utility Itemset Mining
1 Introduction
2 Problem Statement
3 Related Work
4 Examples of SMIM
5 Algorithmic Framework for SMIM
5.1 Projection-Based Algorithms
5.2 Tree-Based Algorithms
5.3 SM-Miner Algorithm
5.4 Empirical Observations
References
TKQ: Top-K Quantitative High Utility Itemset Mining
1 Introduction
2 Related Work
3 Preliminaries and Problem Definition
4 The TKQ Algorithm
5 Experiments
6 Conclusion
References
OPECUR: An Enhanced Clustering-Based Model for Discovering Unexpected Rules
1 Introduction
2 Background
3 Related Work
4 Proposed Method: OPECUR Model
4.1 Generating Association Rule
4.2 Clustering Algorithm
5 Experimental Evaluation
5.1 Experimental Setup
5.2 Experiment 1: Execution Time Comparison
5.3 Experiment 2: Clustering Process Comparison
5.4 Experiment 3: Evaluation of Unexpected Rules
6 Conclusion
References
Tourists Profiling by Interest Analysis
1 Introduction
2 State of the Art
3 Tourism Movement's Data Model
3.1 Sequences Dataset
3.2 Sequential Rule Mining
3.3 Measure of Interest
3.4 Graph Movement Model
4 Community Detection
4.1 Mainstream Nodes
4.2 Spheres of Influence
4.3 Similarity Measure
4.4 Profiling
5 Experiments
5.1 Measure of Interest
5.2 Mainstream Monuments
5.3 Sphere of Influence
5.4 Clustering Analysis
5.5 Discussions
6 Conclusion
References
Extracting High Profit Sequential Feature Groups of Products Using High Utility Sequential Pattern Mining
1 Introduction
1.1 Opinion Mining (OM) and Sentiment Analysis (SA)
1.2 High Utility Sequential Pattern Mining (HUSPM)
1.3 Problem Definition
1.4 Contributions
2 Related Work
3 Proposed High Profit Sequential Feature Groups Based on High Utility Sequences (HPSFG_HUS) System
4 Experimental Evaluation
4.1 Dataset and Implementation Details
4.2 Comparison Analysis of HPSFG_HUS System
5 Conclusion and Future Work
References
Game Achievement Analysis: Process Mining Approach
1 Introduction
2 Background
2.1 Process Mining
2.2 Achievements
3 Related Work
4 Data Preparation
4.1 Steam Achievements Extraction
4.2 Conversion to Event Log
4.3 Game Categorization
4.4 Selected Games
4.5 Data Filtering
5 Analysis of Game Achievements
5.1 Typical Playthrough
5.2 Comparing Player Behaviour
5.3 Game Level Analysis
5.4 Noise Detection
6 Discussion
7 Conclusion
References
A Fast and Accurate Approach for Inferencing Social Relationships Among IoT Objects
1 Introduction
2 Problem Formulation and Basic Definitions
2.1 Basic Definitions
2.2 Problem Statement
3 SociRence: The Proposed Approach
4 Experiments
4.1 Datasets Description
4.2 Baselines
4.3 Performance Evaluation
4.4 Effect of ``distance'' and ``duration'' on the Social Structure
5 Related Works
6 Conclusion and Future Work
References
Graph Mining
A Local Seeding Algorithm for Community Detection in Dynamic Networks
1 Introduction
2 Notations
3 Static Seeding by Local Strategy
3.1 Local Seeding Algorithm
3.2 Local Centrality Measuring
3.3 Hybrid Local Centrality Measuring
4 Dynamic Local Seeding
4.1 Updating Local Centrality
4.2 Dynamic Local Seeding Algorithm
5 Experiments
5.1 Datasets and Evaluation Metrics
5.2 Experimental Results on Static Networks
5.3 Experimental Results on Dynamic Networks
6 Conclusions
References
Clique Percolation Method: Memory Efficient Almost Exact Communities
1 Introduction
2 Related Work
3 Algorithm
3.1 Union-Find Structure
3.2 Exact cpm Algorithm
3.3 Memory Efficient cpm Approximation
4 Analysis
5 Experimental Evaluation
5.1 Comparison with the State of the Art
5.2 Memory Gain of the cpmz Algorithm
5.3 cpmz Communities Are Very Close to cpm Communities
6 Conclusion and Discussions
References
Knowledge Graph Embedding Based on Quaternion Transformation and Convolutional Neural Network
1 Introduction
2 Related Work
3 Method
3.1 Quaternion Space
3.2 Constructing Quaternions of Entities and Relations
3.3 Convolutional Network Designed
3.4 Definition of Loss Function
4 Experiments
4.1 Experimental Setup
4.2 Evaluation Protocol
4.3 Results
4.4 Ablation Study
5 Conclusion
References
Text-Enhanced Knowledge Graph Representation Model in Hyperbolic Space
1 Introduction
2 Related Work
3 Methodology
3.1 Entity Annotation
3.2 Textual Context Embedding
3.3 Hyperbolic Space Modeling
3.4 Representation Training
4 Experiment
4.1 DateSet
4.2 Evaluation Protocol
4.3 Link Prediction
5 Conclusion
References
Relations Reconstruction in a Knowledge Graph of a Socioeconomic System
1 Introduction
2 Problem Statement
3 Related Work
4 Dataset and Preprocessing
4.1 Ontology Construction
4.2 Entity Matching
5 Experiments
6 Results
7 Conclusion
References
A Knowledge Enabled Data Management Method Towards Intelligent Police Applications
1 Introduction
2 Related Concepts and Technologies
2.1 Knowledge Graph
2.2 Ontology
3 SmartHotel Overview
3.1 ShDO
3.2 Knowledge Extraction
3.3 Knowledge Fusion
3.4 Reasoning Rules
4 Experiments
4.1 Purpose
4.2 Datasets
4.3 Experimental Results and Analysis
5 Related Work
6 Conclusion
References
Text Mining
Sparse Generalized Dirichlet Prior Based Bayesian Multinomial Estimation
1 Introduction
2 Preliminary Definitions
3 The Proposed Approach
4 Experimental Results
4.1 Emotion Prediction in Poetry Context
4.2 Modeling the Flow of Emotions Related to Natural Disasters
5 Conclusion
References
I Know You Better: User Profile Aware Personalized Dialogue Generation
1 Introduction
2 Related Work
2.1 Meta-learning
2.2 Personalized Dialogue Generation
3 Personalized Dialogue Generation
3.1 Profile Aware Dialogue Generation
3.2 Sparse Profile Dialogue Generation
4 Experiment
4.1 Dataset
4.2 Baselines
4.3 Implementation Details
4.4 Evaluation Metrics
4.5 Evaluation Results
4.6 Case Study
5 Conclusion
References
Label-Value Extraction from Documents Using Co-SSL Framework
1 Introduction
2 Related Work
3 Proposed Co-SSL Label-Value Extraction Framework
3.1 Candidate Extraction
3.2 Candidate Context Extraction
3.3 Data Augmentation
3.4 Semi-supervised Learning for the Co-SSL Framework
3.5 Implementation Details
4 Datasets and Protocols
5 Results and Analysis
6 Conclusion and Future Work
References
Entity Relations Based Pointer-Generator Network for Abstractive Text Summarization
1 Introduction
2 Related Work
3 Preliminaries
3.1 Pointer-Generator Network
3.2 Graph Attention Network
4 The Proposed Model
4.1 Informative OpenIE Triples Selection Algorithm
4.2 Entity Relations Graph Attention Network
4.3 Entity-Focused Attention Method
5 Experiments
5.1 Datasets
5.2 Data Preprocessing
5.3 Impementation Details
5.4 Quantitative Results
5.5 Ablation Studies
6 Conclusion
References
Linguistic Dependency Guided Graph Convolutional Networks for Named Entity Recognition
1 Introduction
2 Related Work
3 Model
3.1 BiLSTM-CRF
3.2 GCN
3.3 SDP-BiLSTM-GCN-CRF
4 Experiment
4.1 Datasets
4.2 Experiment Setup
4.3 Results
5 Analysis
6 Conclusion
References
Multimedia and Time Series Data Mining
CS-Siam: Siamese-Type Network Tracking Method with Added Cluster Segmentation
1 Introduction
2 Related Works
2.1 Siamese Network Based Trackers
2.2 Image Segmentation Based on Clustering
3 CS-Siam
3.1 Clustering Image Segmentation and Input
3.2 Siamese Network Structure
4 Experimental Results
4.1 Implementation Details
4.2 Dataset
4.3 Comparison Model
4.4 Evaluation Metrics
4.5 Result on OTB2015
4.6 Result on VOT2018
5 Conclusion
References
On Group Theory and Interpretable Time Series Primitives
1 Introduction
2 Preliminaries
3 Extracting Shapeoids in SAX
3.1 Lexical Shapeoids
4 Group Theory and Shapeoid Extraction
5 Conclusion and Discussion
References
Target Detection in Infrared Image of Transmission Line Based on Faster-RCNN
1 Introduction
2 Target Detection Algorithm Based on Infrared Image
2.1 Transmission Line Target Detection Algorithm
2.2 Faster-RCNN Structure Parameter Selection Optimization
3 Experiment
3.1 Dataset Establishment
3.2 Analysis of Results
3.3 Experiment
4 Conclusion
References
Automatic Quality Improvement of Data on the Evolution of 2D Regions
1 Introduction
2 Data Quality Improvement
2.1 Creating Quadtree-Based Time Series
2.2 Identifying and Removing Inconsistent Data
3 Experimental Evaluation
3.1 Datasets and Tools
3.2 Quadtree Generation
3.3 Building the Time Series
3.4 Consistent Data Selection
4 Related Work
5 Conclusions and Future Work
References
Cross-modal Data Linkage for Common Entity Identification
1 Introduction
2 Related Work
3 Problem Definition
4 ICE: Proposed Method
4.1 Record Extraction
4.2 Entity Scoring
4.3 Caption Generation
4.4 Overall Approach
5 Case Study and Experimental Analysis
5.1 Experimental Results and Analysis
6 Conclusions and Future Work
References
Modeling of the Digital Class-D Amplifier Based on Deep Double Feedback Elman Neural Network
1 Introduction
2 Characteristics of the Digital Class-D Amplifier
3 RBM
4 Elman Neural Network
4.1 Traditional Elman Neural Network
4.2 Double Feedback Elman Neural Network
5 Principle of New Model and Analysis of Simulation Results
5.1 Deep Double Feedback Elman Neural Network
5.2 Simulation Result Analysis
6 Conclusion
References
A Novel Face Detection Framework Based on Incremental Learning and Low Variance Directions
1 Introduction
2 Related Works
3 Proposed Framework
3.1 Face Extraction
3.2 Feature Extraction
3.3 Classification
4 Experimental Results
4.1 Datasets Used
4.2 Experimental Protocol
4.3 Results and Discussion
5 Conclusion
References
Classification, Clustering and Recommendation
Supervised Contrastive Learning for Product Classification
1 Introduction
2 Related Work
2.1 Deep Learning for Product Classification
2.2 Contrastive Learning
2.3 Optical Character Recognition (OCR)
3 Proposed Model
4 Experiment
4.1 Datasets
4.2 Training the Model
4.3 Evaluation
5 Conclusion
References
Balanced Spectral Clustering Algorithm Based on Feature Selection
1 Introduction
2 Related Work
2.1 Notations
2.2 Exclusive Lasso
2.3 Spectral Clustering
3 The Proposed Method
3.1 The Details of Our Algorithm
3.2 Optimization of the Algorithm
4 Experimental Analysis
4.1 Datasets and Evaluation Metrics
4.2 Analysis and Comparison of the Experiment Results
4.3 Convergence Analysis
5 Conclusion
References
Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
1 Introduction
2 Background
2.1 Recommendation Systems
2.2 Recommender System Context Ontology
2.3 Contextual Ontological User Profile
3 Related Work
3.1 Ontology-Based Recommender Systems
3.2 Cross-domain Recommender Systems
4 Context-Aware and Multi-domain Recommendations
5 Datasets
6 Results and Discussion
7 Conclusions and Future Work
References
A Relevance Feedback-Based Approach for Non-TI Clustering
1 Introduction
2 Theoretical Concepts of CQQL
3 Weighting of CQQL Conditions
4 Social Network Clustering
5 Relevance Feedback
6 Weight Learning
7 Clustering Properties
8 Quality Measure for Social Network Clustering
9 Experiments
10 Conclusion and Future Work
References
Scalable Nonlinear Mappings for Classifying Large Sparse Data
1 Introduction
2 Classify Large Sparse Data
2.1 Problem Formulation
2.2 Previous Works
3 Approximate Feature Mappings
4 Experiments
5 Conclusion
References
Constrained Energy Minimization for Hyperspectral Multi-target Detection Based on Ensemble Learning
1 Introduction
2 Constrained Energy Minimization (CEM)
3 Improved Multi-target Constrained Energy Minimization Algorithm (IMTCEM)
4 Hyperspectral Target Detection via Ensemble Learning Based Multi-objective Constrained Energy Minimization
5 Experimental Results and Analysis
5.1 Dataset
5.2 Detection Results and Evaluations
6 Conclusion
References
Author Index

Systemvoraussetzungen

Als PDF speichern Als Link merken