All the World's a (Hyper)Graph: A Data Drama

06/16/2022
by   Corinna Coupette, et al.
74

We introduce Hyperbard, a dataset of diverse relational data representations derived from Shakespeare's plays. Our representations range from simple graphs capturing character co-occurrence in single scenes to hypergraphs encoding complex communication settings and character contributions as hyperedges with edge-specific node weights. By making multiple intuitive representations readily available for experimentation, we facilitate rigorous representation robustness checks in graph learning, graph mining, and network analysis, highlighting the advantages and drawbacks of specific representations. Leveraging the data released in Hyperbard, we demonstrate that many solutions to popular graph mining problems are highly dependent on the representation choice, thus calling current graph curation practices into question. As an homage to our data source, and asserting that science can also be art, we present all our points in the form of a play.

READ FULL TEXT VIEW PDF

Authors

page 5

page 8

01/02/2020

Deep Learning for Learning Graph Representations

Mining graph data has become a popular research topic in computer scienc...
05/11/2022

A Survey on Fairness for Machine Learning on Graphs

Nowadays, the analysis of complex phenomena modeled by graphs plays a cr...
09/27/2018

Deep Graph Infomax

We present Deep Graph Infomax (DGI), a general approach for learning nod...
11/17/2018

Representation Mixing for TTS Synthesis

Recent character and phoneme-based parametric TTS systems using deep lea...
03/12/2021

On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions

In this work we formalize the (pure observational) task of predicting no...
09/30/2020

Spectral Embedding of Graph Networks

We introduce an unsupervised graph embedding that trades off local node ...
03/28/2020

A Dataset of Dockerfiles

Dockerfiles are one of the most prevalent kinds of DevOps artifacts used...

Code Repositories

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.

References