1 min readfrom Machine Learning

An interactive semantic map of the latest 10 million published papers [P]

Our take

Explore the cutting-edge interactive semantic map of the latest 10 million published papers, designed to navigate the intricate scientific landscape through spatial exploration. Powered by embeddings from OpenAlex and enhanced with SPECTER 2, this tool employs UMAP for dimensionality reduction and Voronoi partitioning to create distinct semantic neighborhoods. Users can engage with an analytics layer to rank institutions, authors, and topics while utilizing keyword and semantic queries. Experience this innovative resource for free at The Global Research Space, and your feedback is always welcome!
An interactive semantic map of the latest 10 million published papers [P]
An interactive semantic map of the latest 10 million published papers [P]

I built a map to help navigate the complex scientific landscape through spatial exploration.

How it works:

Sourced the latest 10M papers from OpenAlex and generated embeddings using SPECTER 2 on titles and abstracts.

Reduced dimensionality with UMAP, then applied Voronoi partitioning on density peaks to create distinct semantic neighborhoods.

The floating topic labels are generated via custom labelling algorithms (definitely still a work in progress!).

There is also support for both keyword and semantic queries, and there's an analytics layer for ranking institutions, authors, and topics etc.

For anyone who wants to try the interactive map, it is free to use at The Global Research Space

Any feedback or suggestions is welcome!

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