Challenges in Machine Generation of Analytic Products from Multi-Source Data Proceedings of a Workshop (2017) / Chapter Skim
Currently Skimming:
1 Introduction
1 Introduction
Pages 1-2
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 1... ...
More than 300 people registered to participate in the workshop either in person or online. Workshop speakers and participants discussed research challenges related to machine-based methods for generating analytic products and for automating the evaluation of these products, with special attention to learning from small data,2 using multi-source data, adversarial learning,3 and understanding the human–machine relationship.
|
From page 2... ...
The views contained in this proceedings are those of the individual workshop participants and do not necessarily represent the views of the participants as a whole, the planning committee, or the National Academies of Sciences, Engineering, and Medicine. In addition to the summary provided here, materials related to the workshop, including videos of presentation and discussion sessions, can be found at http://sites.nationalacademies.org/DEPS/icsb/DEPS_180349 or https://vimeo.com/album/4730093.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.