The research, recently published in the journal ) The technology could, however, be used in the near future to tackle a long-standing problem for scientists -- how to keep up with the latest research.
“The problem of making sense of the millions of scientific papers published every year is fundamental to accelerating scientific progress,” said Niki Kittur, professor at the Human-Computer Interaction Institute at Carnegie Mellon University, who was not involved in the research.
This infection, termed ‘baylisascariasis,’ kills mice, has endangered the allegheny woodrat." Summarization might save scientists time, but it is not effective in helping scientists identify new targets for research, said Costas Bekas, manager of the Foundations of Cognitive Computing group at IBM-Research Zurich.
Bekas’s team is developing what they call “cognitive discovery” tools, which extract knowledge not only from the text of research papers but also from the images and graphs within them.
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Over 90 percent of raccoons in Santa Barbara play host to this parasite." The RUM summary was easier to read than one generated using a more established technique called long short-term memory (LSTM), which looked like this: "Baylisascariasis, kills mice, has endangered the allegheny woodrat and has caused disease like blindness or severe consequences.
This infection, termed ‘baylisascariasis,’ kills mice, has endangered the allegheny woodrat and has caused disease like blindness or severe consequences.
The technology could help scientists quickly understand where knowledge gaps lie, which he said is a new frontier in research and development.
Charles Dhanaraj, executive director of the Center for Translational Research in Business at Temple University's Fox School of Business, believes AI will help improve the efficacy of research, but notes it is unrealistic to assume that AI could, for example, read 200 research papers and spit out a perfect one-page literature review.