From Security to Community Detection in Social Networking Platforms
This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while pr...
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| Other Authors: | , , |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2019.
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| Edition: | 1st ed. 2019. |
| Series: | Lecture Notes in Social Networks,
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-030-11286-8 |
Table of Contents:
- Chapter1. Real-world application of ego-network analysis to evaluate environmental management structures
- Chapter2. An Evolutionary Approach for Detecting Communities in Social Networks
- Chapter3. On Detecting Multidimensional Communities
- Chapter4. Derivatives in Graph Space with Applications for Finding and Tracking Local Communities
- Chapter5. Graph Clustering Based on Attribute-aware Graph Embedding
- Chapter6. On Counting Triangles through Edge Sampling in Large Dynamic Graphs
- Chapter7. Generation and Corruption of Semi-structured and Structured Data
- Chapter8. A Data Science Approach to Predict the Impact of Collateralization on Systemic Risk
- Chapter9. Mining actionable information from security forums: the case of malicious IP addresses
- Chapter10. Temporal Methods to Detect Content-Based Anomalies in Social Media.