On Bi-gram Graph Attributes

We propose a new approach to text semantic analysis and general corpus using, as termed in this article, "bi-gram graph" representation of corpus. The different attributes derived from graph theory are measured analyzed unique insights or against other graphs. observe vast domain tools algorithms that can be developed on top the representation; creating such proves computationally cheap, much heavy lifting is achieved via basic calculations. Furthermore, we showcase use-cases for bi-gram graphs how scalable it when dealing with large datasets.