ingoscholtes / kdd2018-tutorial

Companion repository for the KDD'18 hands-on tutorial on Higher-Order Data Analytics for Temporal Network Data

Beyond Graph Mining: Higher-Order Data Analytics for Temporal Network Data

In this repository, wou will find all material needed to complete the KDD'18 hands-on tutorial on Higher-Order Data Analytics for Temporal Network Data.

A summary of the tutorial can be found in the detailed proposal.

A detailed tutorial schedule as well as step-by-step setup instructions can be found on the tutorial website.

While you can manually download all necessary files, we strongly recommend to clone this repository to obtain a local, sychronised copy of all material via git. Assuming you have a local git installation, you can do this as follows:

git clone https://github.com/IngoScholtes/kdd2018-tutorial

If you don't have git installed already, here you can find information on how to set up git.

Prior to the hands-on tutorial, you will get access to skeleton python files, that we will complete together throughout the tutorial sessions. At specific *synchronisation points, we will push a commit of the current solution to this gitHub repository. You can thus simply execute the terminal command

git pull

in the directory of your local copy to receive a sample solution that is growing as the tutorial advances.

kdd2018-tutorial's Issues

1.4 Temporal Network Analysis and Visualisation in pathpy

The tutorials look amazing and are the kind of content I wish all packages have, unfortunately I am unable to run many of them.

Are lots of the functions now out of date?

For instance, the second chunk of code does not run as in the tutorial.

It can be made to run with the following, but the output is different:

t.add_edge('a', 'b',ts= 1)
t.add_edge('b', 'a',ts= 2)
t.add_edge('b', 'c',ts= 3)
t.add_edge('d', 'c',ts= 4)
t.add_edge('c', 'd',ts= 5)
t.add_edge('c', 'b',ts= 6)
print(t)