June 2024
Intermediate to advanced
290 pages
7h 52m
English
Content preview from Modern Graph Theory Algorithms with Python
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Part 4: Advanced Applications
Part 4 introduces more advanced algorithms to wrangle network problems, including graph neural networks, vertex clustering, Bayesian networks, ontology web language, subgraphs mining, and graph databases. The problems tackled in this part include the clustering of social network vertices by demographic and network structure factors, understanding the evolution of substance misuse, mining causal pathways related to student learning outcomes, creating gene ontologies, comparing the language classifications of Nilo-Saharan languages, mapping food webs, and creating movie databases with a variety of relationships.
Of note in Part 4 are Chapters 13 and 14. Chapter 13 combines concepts from throughout this book to construct ...
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