Feb. 22: Event on Machine Learning & Cultural Heritage

Join us online on Tuesday, February 22 at 4:30 pm for “Novel Machine Learning Methods for Computing Cultural Heritage: An Interdisciplinary Approach” with Benjamin Lee (University of Washington). (REGISTER)

The event responds to an important challenge for those who engage with digital collections. Whereas widespread efforts over the past two decades have drastically improved digital access to cultural heritage collections, the collections—which frequently contain millions of items and often suffer from imperfect metadata—can often be difficult to navigate and analyze.

Lee will share how his project, Newspaper Navigatorre-imagines how humanists, social scientists, and the public can engage with visual content in millions of digitized historic newspaper pages. He will also introduce his ongoing work surrounding the development of open faceted search systems for petabyte-scale web archives and elaborate on how his research can extend to a wide range of digitized and born-digital collections.

The talk will be moderated by Jim Casey (Penn State) and Tianyi Wang (Princeton). Registration is required.

This event is part of the Machine Learning + Humanities Working Group Series and is co-sponsored by the Data-Driven Social Science Initiative and the Center for Statistics and Machine Learning.

You are also invited to join the Working Group either online or in person at the CDH the following day, February 23, at 12:30 pm for a discussion of the event. Details and registration for the lunchtime event are available on our website.

Carousel Image from the Newspaper Navigator.

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