Scaling Machine-Assisted Description of Historical Records

One of the questions I’ve been grappling with as part of the Archival Connections research project is simple: Is there a future for the finding aid?  I’m inclined to think not, at least not in the form we are used to.

Looking to the future, I recently had the chance to propose something slightly different, and have proposed a potential project for funding via an Amazon Research Grant. While the jury is still out on the proposal (an answer is coming in mid-December), I’d like to share a copy of the proposal, Scaling Machine-Assisted Description of Historical Materials.

The idea I describe there seeks to build on an emergent digital repository and library infrastructure that is being built by the University of Illinois Library.  It seeks to integrate natural language processing and named entity recognition elements to index and provide relational browsing pathways alongside file-system access.  I’ll  have more to say about this at the Society of Indiana Archivists meeting tomorrow.

One thought on “Scaling Machine-Assisted Description of Historical Records”

  1. I have begun to apply Named Entity Recognition (NER) functionally to the full text of library collections. This results in a WHOLE LOT of additional names, places, and organizations from which to enhance description and/or discovery. My question is, which one(s) of these entities or what characteristics ought particular entity have to make the worth including in a description or making extra-accessible via discovery? I’m thinking of some sort of mathematical significance, such as a ratio of frequency to size of text. What do you think?

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