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Record Nr. |
UNINA9910777303003321 |
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Autore |
Neuhaus Michel |
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Titolo |
Bridging the gap between graph edit distance and kernel machines [[electronic resource] /] / Michel Neuhaus, Horst Bunke |
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Pubbl/distr/stampa |
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Singapore ; ; Hackensack, NJ, : World Scientific, c2007 |
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ISBN |
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1-281-91905-5 |
9786611919054 |
981-277-020-8 |
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Descrizione fisica |
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1 online resource (244 p.) |
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Collana |
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Series in machine perception and artificial intelligence ; ; v. 68 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Pattern recognition systems |
Matching theory |
Machine learning |
Kernel functions |
Graph theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Extended and revised version of the first author's PhD thesis. |
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Nota di bibliografia |
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Includes bibliographical references (p. 221-230) and index. |
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Nota di contenuto |
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Preface; Contents; 1. Introduction; 2. Graph Matching; 2.1 Graph and Subgraph; 2.2 Exact Graph Matching; 2.3 Error-Tolerant Graph Matching; 3. Graph Edit Distance; 3.1 Definition; 3.2 Edit Cost Functions; 3.2.1 Conditions on Edit Costs; 3.2.2 Examples of Edit Costs; 3.3 Exact Algorithm; 3.4 Efficient Approximate Algorithm; 3.4.1 Algorithm; 3.4.2 Experimental Results; 3.5 Quadratic Programming Algorithm; 3.5.1 Algorithm; 3.5.1.1 Quadratic Programming; 3.5.1.2 Fuzzy Edit Path; 3.5.1.3 Quadratic Programming Edit Path Optimization; 3.5.2 Experimental Results; 3.6 Nearest-Neighbor Classification |
3.7 An Application: Data-Level Fusion of Graphs 3.7.1 Fusion of Graphs; 3.7.2 Experimental Results; 4. Kernel Machines; 4.1 Learning Theory; 4.1.1 Empirical Risk Minimization; 4.1.2 Structural Risk Minimization; 4.2 Kernel Functions; 4.2.1 Valid Kernels; 4.2.2 Feature Space Embedding and Kernel Trick; 4.3 Kernel Machines; 4.3.1 Support Vector Machine; 4.3.2 Kernel Principal Component Analysis; 4.3.3 |
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Kernel Fisher Discriminant Analysis; 4.3.4 Using Non-Positive De nite Kernel Functions; 4.4 Nearest-Neighbor Classification Revisited; 5. Graph Kernels; 5.1 Kernel Machines for Graph Matching |
5.2 Related Work 5.3 Trivial Similarity Kernel from Edit Distance; 5.4 Kernel from Maximum-Similarity Edit Path; 5.5 Diffusion Kernel from Edit Distance; 5.6 Zero Graph Kernel from Edit Distance; 5.7 Convolution Edit Kernel; 5.8 Local Matching Kernel; 5.9 Random Walk Edit Kernel; 6. Experimental Results; 6.1 Line Drawing and Image Graph Data Sets; 6.1.1 Letter Line Drawing Graphs; 6.1.2 Image Graphs; 6.1.3 Diatom Graphs; 6.2 Fingerprint Graph Data Set; 6.2.1 Biometric Person Authentication; 6.2.2 Fingerprint Classification; 6.2.3 Fingerprint Graphs; 6.3 Molecule Graph Data Set |
6.4 Experimental Setup 6.5 Evaluation of Graph Edit Distance; 6.5.1 Letter Graphs; 6.5.2 Image Graphs; 6.5.3 Diatom Graphs; 6.5.4 Fingerprint Graphs; 6.5.5 Molecule Graphs; 6.6 Evaluation of Graph Kernels; 6.6.1 Trivial Similarity Kernel from Edit Distance; 6.6.2 Kernel from Maximum-Similarity Edit Path; 6.6.3 Diffusion Kernel from Edit Distance; 6.6.4 Zero Graph Kernel from Edit Distance; 6.6.5 Convolution Edit Kernel; 6.6.6 Local Matching Kernel; 6.6.7 Random Walk Edit Kernel; 6.7 Summary and Discussion; 7. Conclusions; Appendix A Graph Data Sets; A.1 Letter Data Set; A.2 Image Data Set |
A.3 Diatom Data Set A.4 Fingerprint Data Set; A.5 Molecule Data Set; Bibliography; Index |
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Sommario/riassunto |
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In graph-based structural pattern recognition, the idea is to transform patterns into graphs and perform the analysis and recognition of patterns in the graph domain - commonly referred to as graph matching. A large number of methods for graph matching have been proposed. Graph edit distance, for instance, defines the dissimilarity of two graphs by the amount of distortion that is needed to transform one graph into the other and is considered one of the most flexible methods for error-tolerant graph matching.This book focuses on graph kernel functions that are highly tolerant towards structural |
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2. |
Record Nr. |
UNINA9910492143803321 |
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Titolo |
Internet of Things : Cases and Studies / / edited by Fausto Pedro García Márquez, Benjamin Lev |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
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ISBN |
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Edizione |
[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (312 pages) |
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Collana |
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International Series in Operations Research & Management Science, , 2214-7934 ; ; 305 |
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Disciplina |
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Soggetti |
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Operations research |
Management science |
Business information services |
Operations Research and Decision Theory |
Operations Research, Management Science |
Business Information Systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction to Internet of Things: Cases and Studies -- Chapter 1: Blockchain as a complementary technology for the Internet of Things: A survey -- Chapter 2: Enablers and inhibitors for IoT implementation -- Chapter 3: The combination of AI, Blockchain and the internet of things for patient relationship management -- Chapter 4: Bibliomeric characteristics of highly cited papers on Internet of Things assessed with Essential Science Indicators -- Chapter 5: A Macroeconomic Aspect of IoT services: Their Marginal Costs -- Chapter 6: Biclustering Analysis of Countries using COVID-19 Epidemiological Data -- Chapter 7: IoT Applications in Health Care -- Chapter 8: An interactive visiting system using BLE devices -- Chapter 9: Systematic Market and Asset Liquidity Risk Processes for Machine Learning: Robust Modeling Algorithms for Multiple-Assets Portfolios -- Chapter 10: Context Modelling in Ambient Assisted Living: Trends and Lessons -- Chapter 11: Design of Algorithm for IoT Based Application: CaseStudy on Intelligent Transport Systems -- Chapter 12: Examining Spatial Movement Patterns of Travelers: Cases in Tourist Destinations -- |
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Chapter 13: Use of UAVs, computer vision and IoT for traffic analysis. |
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Sommario/riassunto |
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This book provides relevant theoretical frameworks and the latest empirical research findings of Operations Research/Management Science applied to Internet of Things. This book identifies and describes ways in which OR and MS have been applied and influenced the development of IoT. Examples are from smart industry; city; transportation; home and smart devices. It discusses future applications, trends, and potential benefits of this new discipline. It is written for professionals who want to improve their understanding of the strategic role of IoT at various levels of the organization, that is, IoT at the global economy level, at networks and organizations level, at teams and work groups, at information systems and, finally, IoT at the level of individuals, as players in the networked environments. . |
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