Graph Theory and Network Science (Aurelius)
When a post that starts out:
Graph theory and network science are two related academic fields that have found application in numerous commercial industries. The terms ‘graph’ and ‘network’ are synonymous and one or the other is favored depending on the domain of application. A Rosetta Stone of terminology is provided below to help ground the academic terms to familiar, real-world structures.
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And ends:
Ranking web pages is analogous to determining the most influential people in a social network or finding the most relevant concepts in a knowledge network. Finally, all these problems are variations of one general process—graph traversing. Graph traversing is the simple process of moving from one vertex to another vertex over the edges in the graph and either mutating the structure or collecting bits of information along the way. The result of a traversal is either an evolution of the graph or a statistic about the graph.
The tools and techniques developed by graph theorists and networks scientists has an astounding number of practical applications. Interestingly enough, once one has a general understanding of graph theory and network science, the world’s problems start to be seen as one in the same problem.
With about as nice an introduction to why graphs/networks are important as I have read in a long time, you know it is going to be a good day!
Particularly when the source cited on graph traversal is none other than Marko A. Rodriguez and Peter Neubauer of Neo4j fame. (They may be famous for other reasons as well but you will have to contribute those.) (Yes, I noticed who is associated with the site.)
I find the notion of mutating the structure of a graph based on traversal to be deeply interesting and useful in a topic maps context.
[…] in Graph Theory and Network Science and one of those bibliography items I have been meaning to pick […]
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