Graph-Based Representations in Pattern Recognition

Name: Graph-Based Representations in Pattern Recognition | 12th IAPR-TC-15 International Workshop, GbRPR 2019, Tours, France, June 19-21, 2019, Proceedings
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12th IAPR-TC-15 International Workshop, GbRPR 2019, Tours, France, June 19-21, 2019, Proceedings

Donatello Conte Jean-Yves Ramel Pasquale Foggia(Editor)

Springer (Publisher)

Published on 10. June 2019

X, 247 pages

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978-3-030-20081-7 (ISBN)

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Content

Intro
Preface
Organization
Contents
Experimental Evaluation of Subgraph Isomorphism Solvers
1 Introduction
2 Experimental Set-Up
3 Does the Solving Time Depend on Graph Sizes?
4 Where Are the Hard Instances?
5 Experimental Comparison of the Solvers
6 Combining Solvers to Take the Best of Them
7 Conclusion
References
GEDLIB: A C++ Library for Graph Edit Distance Computation
1 Introduction
2 Overall Architecture
3 User Interface
4 Abstract Classes for Implementing GED Algorithms
5 Abstract Class for Implementing Edit Costs
6 Conclusions and Future Work
References
Learning the Graph Edit Costs: What Do We Want to Optimise?
Abstract
1 Introduction
2 Attributed Graphs and Graph Edit Distance
3 Learning Methods and Objective Functions
4 Experimental Evaluation
5 The Conclusions
Acknowledgments
References
Sub-optimal Graph Matching by Node-to-Node Assignment Classification
1 Introduction
2 Definitions
2.1 Attributed Graphs and Graph Edit Distance
2.2 Approximating the Graph Edit Distance
3 Learning Graph Matching
3.1 Learning the Edit Costs and Graph Embedding
3.2 From Edit Costs Estimation to Node Assignment Classification
3.3 Training the Classifier
4 Experimental Evaluation
4.1 Database Description
4.2 Graph Matching Performance
4.3 Runtime Analysis
5 Conclusions
References
Cross-Evaluation of Graph-Based Keyword Spotting in Handwritten Historical Documents
1 Introduction
1.1 Related Work
1.2 Contribution
2 Graph-Based Keyword Spotting
2.1 Image Preprocessing
2.2 Handwriting Graphs
2.3 Graph Matching
2.4 Ensemble Methods
3 Experimental Evaluation
3.1 Experimental Setup
3.2 Cross-Evaluation
3.3 Ensemble Methods
4 Conclusion and Outlook
References
Graph Edge Entropy in Maxwell-Boltzmann Statistics for Alzheimer's Disease Analysis
1 Introduction
2 Graph Representation
2.1 Preliminaries
2.2 Von Neumann Edge Entropy
3 Thermodynamic Statistics and Global Entropy Decomposition
3.1 Thermodynamic Entropy
3.2 Maxwell-Boltzmann Statistics
3.3 Edge Entropy Decomposition
4 Experiments and Evaluations
4.1 Dataset
4.2 Experimental Results
5 Conclusion
References
Solving the Graph Edit Distance Problem with Variable Partitioning Local Search
1 Introduction
2 GED Definition and F3 Formulation
2.1 GED Problem Definition
2.2 Mixed Integer Linear Program
2.3 F3 Formulation
3 VPLS Heuristic
3.1 Main Features of VPLS
3.2 VPLS for the GED Problem
4 Computational Experiments
5 Conclusion
References
A Database and Evaluation for Classification of RNA Molecules Using Graph Methods
1 Introduction
2 Related Work
3 Database
4 RNA Representation
5 Classification Methods
5.1 Sequence-Based Methods
5.2 Weisfeiler-Lehman Optimal Assignment (WL-OA)
5.3 Shortest Path Embedding
5.4 All Paths and Cycles Embedding(APC)
6 Results
7 Conclusion
References
Event Prediction Based on Unsupervised Graph-Based Rank-Fusion Models
1 Introduction
2 Preliminaries
3 Graph-Based Rank Fusion for Event Prediction
3.1 Fusion Graph Extraction
3.2 Fusion Graph Embedding
3.3 Event Prediction from Fusion Vectors
4 Experimental Evaluation
4.1 Validation Scenario
4.2 Effectiveness Results
5 Conclusions
References
Generalized Median Graph via Iterative Alternate Minimizations
1 Introduction
2 Graph Transformations and Graph Edit Distance
3 Estimating a Generalized Median Graph
3.1 Proposed Algorithm
3.2 Updating Vertex Attributes
3.3 Updating Edges and Their Attributes
4 Experimental Results
5 Conclusion
References
An Hypergraph Data Model for Expert Finding in Multimedia Social Networks
1 Introduction
2 Related Work
3 Modeling Multimedia Social Networks
3.1 Basic Definitions
3.2 Relationships
3.3 Hypergraph Building
3.4 Centrality Measures for Expert Finding
4 System Architecture
5 Results and Discussion
6 Conclusion
References
On-Line Learning the Edit Costs Based on an Embedded Model
1 Introduction
2 Graph Edit Distance
3 Learning the Graph Edit Costs
3.1 Off-Line Learning the Graph Edit Costs
3.2 On-Line Learning the Graph Edit Costs
4 Experimental Validation
5 Conclusions
References
Congratulations! Dual Graphs Are Now Orientated!
1 Introduction
2 Orienting the Primal Graph
2.1 Contracting Plateaus
3 Orientation of Dual Graphs
4 Merging of Two Slope Regions
4.1 Orientation of Level Curves Shared by Multiple Monotonic Paths
5 Conclusion
References
A Parallel Algorithm for Subgraph Isomorphism
1 Introduction
2 VF3-Light: The Sequential Algorithm
2.1 Graphs and Graph Matching
2.2 VF3-Light
3 Parallel Algorithms
4 Experiments
5 Conclusions
References
Local Binary Pattern Based Graph Construction for Hyperspectral Image Segmentation
1 Introduction
2 Preliminaries
2.1 Graph
2.2 Local Binary Patterns
3 LBP-based Graph Construction
4 HSI Segmentation
5 Experiments
6 Conclusion
References
A Parallel MCMC Algorithm for the Balanced Graph Coloring Problem
1 Introduction
2 Parallel MCMC Sampling
2.1 Notations
2.2 Markov Chain Monte Carlo for Sampling Colorings
2.3 Generation of Proposal Color
2.4 Algorithm
3 Numerical Simulations
3.1 CUDA Parallel Implementations
3.2 Performances on ER Graphs
4 Conclusions
References
An Attributed Graph Embedding Method Using the Tree-Index Algorithm
1 Introduction
2 A Vertex Label Strengthening Method
2.1 A Tree-Index Based Vertex Label Strengthening Method
2.2 A Label Shannon Entropy
3 The Embedding Method for Attributed Graphs
3.1 The Attributed Graph Embedding Method Through the TI Algorithm
3.2 The Computational Complexity Analysis
4 Experimental Evaluation
4.1 Datasets
4.2 Experiments on Graph Datasets
4.3 Stability Evaluation
5 Conclusion
References
A Graph-Theoretic Framework for Summarizing First-Person Videos
1 Introduction
2 Related Works
3 Proposed Method
3.1 Graph Based Center-Surround Model
3.2 Frame Based Feature Extraction
3.3 Construction of the Video Similarity Graph
3.4 MST Based Improved Clustering
4 Time-Complexity Analysis
5 Experimental Results
5.1 Tuning of the Parameters
5.2 Ablation Study
5.3 Cluster Validation
5.4 Results on SumMe Dataset
5.5 Results on TvSum50 Dataset
6 Conclusion
References
Network Time Series Analysis Using Transfer Entropy
1 Introduction
2 Entropic Analysis of Information Flow on Edges
2.1 Preliminaries
2.2 Information Flow Between Time Series and Edge Weighting
2.3 Embedding Using Multidimensional Scaling
3 Experiments
3.1 Graph Entropy
3.2 Network Embedding
4 Conclusion
References
Reconstructing Objects from Noisy Images at Low Resolution
1 Introduction
2 Related Work
2.1 Related Reconstruction Approaches
2.2 Related Segmentation Algorithms
2.3 Reconstructing r-regular Objects from Ideal Images
3 Noisy Images
4 A Greedy Local Algorithm
5 Similarity Weights
6 Experiments
7 Discussion
References
Network Embedding by Walking on the Line Graph
1 Introduction
2 Classic vs Neural Embeddings
2.1 Classic Embeddings
2.2 Neural Embeddigs
2.3 LINE and DeepWalk vs node2vec Factorizations
3 Node vs Edges Embedding
3.1 The Line Graph
3.2 Spectral Analysis
4 Experiments and Discussion
4.1 Datasets (Networks)
5 Conclusions
References
Discriminant Manifold Learning with Graph Convolution Based Regression for Image Classification
1 Introduction
2 Related Work
2.1 Notation and Preliminaries
2.2 Manifold Regularized Deep Learning Algorithm (MRDL)
2.3 Graph Convolutional Networks (GCN)
3 Proposed Method
4 Experimental Results
4.1 Datasets
4.2 Experimental Setup
4.3 Method Comparison
5 Conclusion
References
Graph-Based Representations for Supporting Genome Data Analysis and Visualization: Opportunities and Challenges
1 Introduction
2 DNA Analysis Problems
2.1 Genome Assembly
2.2 Sequence Alignment
2.3 Variant Calling and Pangenomics Analysis
3 Graph-Based Representation for DNA Sequences
3.1 Overlap Graphs
3.2 String Graphs
3.3 De Bruijn Graphs
3.4 Genome Alignment Graphs
3.5 Tiled Graphs and Sequence Graphs
3.6 Variation Graphs
4 Graph Based Tools for Genome Analysis
5 Main Issues and Challenges for Use of Graph for DNA Analysis
6 Conclusions
References
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Graph-Based Representations in Pattern Recognition

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