
Method for Combining Data Farming and Data Mining in a Logistics Assistance System for Materials Trading Networks Based on Graph Databases
Cuvillier Verlag eBooks
Published on 11. August 2025
314 pages
978-3-68952-314-5 (ISBN)
System requirements
for PDF without DRM
E-Book Single Licence
You are acquiring a single user licence for this eBook, which you might not transfer. [L]
Available for download
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
Text>
More details
Language
English
Place of publication
Göttingen
Germany
File size
31,57 MB
ISBN-13
978-3-68952-314-5 (9783689523145)
Schweitzer Classification
Other editions
Additional editions

Book
08/2025
1st Edition
Cuvillier Verlag
€167.50
Shipment within 10-15 days
Persons
Content
- Intro
- Contents
- Introduction
- Decision Support in Materials Trading Networks
- Fundamentals of Materials Trading Networks
- Logistics und Supply Chains
- Materials Trading Networks
- Key Performance Indicators in Materials Trading Networks
- Logistics Tasks in Materials Trading
- Data, Information, and Knowledge
- Demarcation of the Terms Data, Information, and Knowledge
- Classification of Data in Materials Trading Networks
- Logistics Assistance Systems in the Context of Materials Trading Networks
- Fundamentals of Information Systems
- Decision Support Systems
- Structure and Methods of Logistics Assistance Systems
- Data Management in Materials Trading Networks
- Database Systems
- Relational and Non-Relational Databases
- Fundamentals of Graph Databases
- Methods in the Context of Simulation-based Data Generation
- Simulation-based Data Generation
- Fundamentals of Simulation
- Data Farming
- Procedure Models in Data Farming
- Phases in Data Farming Procedure Models
- Analysis of Simulation Result Data
- Knowledge Discovery and Data Mining
- Graph Algorithms and Graph Mining
- Graph-based Methods in Materials Trading Networks
- Problem Statement and Research Questions
- Limitations of Previous Research Activities
- Research Approach and Delimitation
- Research Questions
- Data Farming in Logistics Assistance Systems for Materials Trading Networks
- Overview of the Methodological Framework
- Research Design
- Structure and Conceptual Design of the Method
- Architecture of the Logistics Assistance System
- Software Components of the Farming for Mining Logistics Assistance System
- Graph Database System
- Simulation Tool
- Knowledge Discovery Tool
- Method Initialization
- Development of a Specific Procedure Model for Simulation-Based Data Generation
- Derivation of Requirements for Simulation-Based Data Generation
- Selection of a Procedure Model
- Adaptation of the Selected Procedure Model
- Integration of Verification and Validation in the Context of the Method
- Knowledge Discovery in Simulation Result Data in Graph Databases
- Knowledge Discovery in the Context of the Method
- Integration of a Procedure Model for Knowledge Discovery
- Derivation of Requirements and Selection of a Procedure Model for Knowledge Discovery
- Adaptation of a Procedure Model for Knowledge Discovery
- Pattern Verification and Validation using Simulation
- Prototypical Implementation of the Developed Method
- Evaluation of Farming for Mining
- Concept and Goals of the Evaluation
- Introduction to the Use Case
- Application Field 1: Initialization
- Application Field 2: Simulation-based Data Generation
- Task Definition
- Input Data and Model Development
- Design of Experiments
- Experiments and Output Data
- Evaluation
- Verification and Validation
- Application Field 3: Knowledge Discovery and Decision Support
- Data Mining Preparation and Application
- Processing and Visualization of Results for Decision Support
- Verification and Validation
- Critical Reflection
- Summary and Future Research
- References
- List of Figures
- List of Tables
- List of Algorithms
- List of Acronyms
- Data Mining and Graph Mining Tasks, Methods, and Algorithms
- Stochastic Fundamentals
- Descriptive Statistics
- Probability Distributions and Population Parameters
- Inferential Statistics
- Verification and Validation
- Triangle Model for Verification and Validation
- Techniques for Verification and Validation
- Procedure Model for Knowledge Discovery in Databases
- Published Research Publications (Peer-Reviewed)
- Leere Seite
- Leere Seite
System requirements
File format: PDF
Copy protection: without DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook does not use copy protection or Digital Rights Management.
For more information, see our eBook Help page.