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Improving Access to Archival Collections with Automated Entity Extraction
by Kyle Banerjee and Max Johnson
http://journal.code4lib.org/articles/10726/

"The complexity and diversity of archival resources make constructing
rich metadata records time consuming and expensive, which in turn
limits access to these valuable materials. However, significant
automation of the metadata creation process would dramatically reduce
the cost of providing access points, improve access to individual
resources, and establish connections between resources that would
otherwise remain unknown.
Using a case study at Oregon Health & Science University as a lens to
examine the conceptual and technical challenges associated with
automated extraction of access points, we discuss using publically
accessible API’s to extract entities (i.e. people, places, concepts,
etc.) from digital and digitized objects. We describe why Linked Open
Data is not well suited for a use case such as ours. We conclude with
recommendations about how this method can be used in archives as well
as for other library applications."
 

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