Gnuplot is a portable command-line driven graphing utility for Linux, OS/2, MS Windows, OSX, VMS, and many other platforms. The source code is copyrighted but freely distributed (i.e., you don't have to pay for it). It was originally created to allow scientists and students to visualize mathematical functions and data interactively, but has grown to support many non-interactive uses such as web scripting. It is also used as a plotting engine by third-party applications like Octave. Gnuplot has been supported and under active development since 1986.
Students can draw graphs in a coordinate system. This program is good for especially high school students. The program makes it very easy to visualize a function and paste it into another program. Students can do calculations on the functions.
Graph neural networks are intimately related to partial differential equations governing information diffusion on graphs. Thinking of GNNs as PDEs leads to a new broad class of graph ML methods.
The web can be represented by a graph with special regions: SCC, IN, OUT and TENDRILS.
Regions are defined by the link-path-reach from one website to others.
The linkage to and from a website (in- and out-degree) seems to conform the power law, which is also mentioned in this document.
What else is there to say? This code is available under the gpl, so follow those terms. Send back improvements, extensions, and contributions to code@creativesynthesis.net. Otherwise start by modifying the simple.xml file and using this html page.
Graph-based NLP
From Language and Information Technologies
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The goal of this research project is to investigate efficient graph-based representations of text, and explore the application of ranking models based on such graph structures to natural language processing tasks. We bring together methods from computational linguistics and graph-theory, and combine them into a suite of innovative approaches that will improve and ultimately solve difficult problems in natural language processing. Specifically, we are currently working on the application of graph centrality algorithms to problems such as word sense disambiguation, text summarization and keyword extraction.