On Bi-gram Graph Attributes

• URL: http://arxiv.org/abs/2107.02128v1
• Date: Mon, 5 Jul 2021 16:36:19 GMT
• Title: On Bi-gram Graph Attributes
• Authors: Thomas Konstantinovsky, Matan Mizrachi
• Abstract summary: We propose a new approach to text semantic analysis using a "bi-gram graph" representation of a corpus. The different attributes derived from graph theory are measured and analyzed as unique insights or against other corpus graphs.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a new approach to text semantic analysis and general corpus analysis using, as termed in this article, a "bi-gram graph" representation of a corpus. The different attributes derived from graph theory are measured and analyzed as unique insights or against other corpus graphs. We observe a vast domain of tools and algorithms that can be developed on top of the graph representation; creating such a graph proves to be computationally cheap, and much of the heavy lifting is achieved via basic graph calculations. Furthermore, we showcase the different use-cases for the bi-gram graphs and how scalable it proves to be when dealing with large datasets.

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