From: Benjamin Maverick Turley <[log in to unmask]>
Date: Wed, 22 Aug 2018 19:45:09 +0000


*“Alexa, find me a scholarly journal article on nonlinear optics.”*
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Artificial intelligence (AI) and machine learning (ML) is on a trajectory
to quickly replace more traditional means of search. Today’s users ask
questions, make statements, and expect search engines to understand and
return relevant results in a way that provides greater precision with
contextual information and answers.

Researchers and other consumers of scholarly content are among the most
advanced and demanding users of information systems and specialized
repositories.  However, as publishers and content aggregators, we have not
yet advanced search to the point at which we can posit to Google or Alexa,
“find me a scholarly journal article on nonlinear optics.” But we are
advancing toward that goal.

As we prepare our content for semantic search and AI, the adoption of
accurate, structured text for the storage and display of scholarly content
will make it easier to extract, clean, and structure the data in order to
maximize AI, ML and ontological structures.

NFAIS will explore how the scholarly communication community can harness
the technologies and capabilities of AI and ML to reshape the scientific
research community in its August 29th workshop, *Getting Your Content Ready
for Semantic Search and AI*.

Check out this behind the scenes interview of Bob Kasenchak of Access
Innovations:

https://www.youtube.com/watch?v=48d0wdUz7bw&t=269s

In this interview, Bob will provide a look at where we're headed in regards
to artificial intelligence and machine learning, and how we can prepare for
the next generation of search.

For more information visit about the presenters and the semantic web, visit:

https://www.nfais.org/index.php?option=com_mc&view=mc&mcid=72&eventId=547970

*******