‘(It) could potentially be used by journalists to help communicate complex research to the public, though the authors say they aren’t going to be putting journalists out of a job any time soon.‘
A new algorithm for summarizing text could make piles of information easier to absorb, reports INSIDE HIGHER ED.
- Distilling texts is complicated for machines because typically they can’t retain context over long passages.
- This new algorithms uses a new approach. It looks for patterns between words all the way through a document and knits them together. Researchers call their method RUM, for Rotational Unit of Memory. The name describes how meaning is drawn from around a document, like how a sweep-hand works on a clock.
- The research was done at MIT.
- Unlike many systems that use a kind of ‘cut-and-paste’ approach that reduces the number of existing words, RUM appears to generate new sentences while retaining original meaning.
- These are preliminary results and only indicates new research directions.
- Future iterations could be valuable for journalism. Think of applications in radio newscasts, digital signage, and aspects of daily news.
- Many forms of automated summarization today are limited to shorter documents or structured data.
Drowning in Research Reading? AI Could Help
INSIDE HIGHER ED | May 14, 2019 | by Lindsay McKenzie