Features

Rapid Network Analysis

Choose between two powerful algorithms and get fast results.

Search Space Reduction

Quickly get the information you need.

Free to Use

Does it get any better than free?

K-Simple Shortest Paths w/ Multithreading

Find up to 10 paths between two vertices.

Shortest Path MST w/ Multithreading

Find an optimal MST between 2 and 5 vertices.

Graph Visualization

Create insightful visualizations with a click of the button.

About This Project:

This research is an effort to develop visual-graphic interfaces for sense-making of large networks. The goal is to create an algorithmic model and prototype that will allow researchers to study and analyze the hidden patterns in a wide range of networks by identifying and characterizing local communities and connectivity between a set of pre-marked nodes within large networks.

There is a staggering wealth of electronic data that is being generated, collected and stored due to the digital revolution. What scientists lack are meaningful ways of translating this data into useful information and knowledge. This overabundance of data, with largely unknown conclusions, is evident across all academic disciplines, ranging from medicine and epidemiology to advertising and marketing. The question that ultimately needs to be addressed is — how do we better understand and make predictions about the future based on the relationships between these disparate sets of data.

Project Lead

Scott Freitas
safreita@asu.edu
M.S. Computer Science Student ASU

Adviser

Hanghang Tong
htong6@asu.edu
Assistant Professor ASU CIDSE



I would also like to thank Silviu Popovici for helping in the design and implementation of the website front-end.