Dive into dreams and explore the subconscious terrain with GraphXR and Neo4j.

Using dream reports provided by UCSC’s DreamBank, deep learning for NLP and text-to-image generation, we build a dream similarity graph to visualize, identify, and interpret dream clusters.

While the choice of dreams data is a bit tongue-in-cheek, the methodology we use here can be applied in many other domains in order to make sense of large amounts of data, find hidden connections and create compelling visualizations.

See our blogpost with more details including interactive GraphXR visualizations.

Presented at Nodes 2021 Conference. You can find the presentation slides here and all the code to recreate the project in this repository.