Tuesday, November 17, 2015

Analyzing Academic Papers Using Cutting-Edge AI to Find Meaning in Billions of Words

The Allen Institute for Artificial Intelligence is working toward this very goal, and has developed a new tool called Semantic Scholar that can search through millions of computer science papers. The tool, launched today, features ways of refining searches based on information extracted from the text of papers.
 

It is, for instance, possible to narrow a search according to the journal in which a paper was published, or the conference at which it was presented, or by the data set used. Semantic scholar will also show key phrases in a paper.
 

Many academic search engines already exist, among them Google Scholar, Microsoft Academic Search, PubMed, and JSTOR. But these typically only search through papers using keywords and other information that is clearly categorized, such as the publication date.
 

Oren Etzioni, executive director of the Allen Institute, says a lot of pertinent information found in research papers is presented in different ways. The software behind Semantic Scholar was trained to extract different concepts using a variety of machine-learning techniques. “With millions of papers appearing every year, you just can’t keep up with them,” Etzioni says. “So you need some level of understanding.”


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