With Google Scholar, PubMed, and other free academic databases at their fingertips, scientists may feel they have plenty of resources to trawl through the ever-growing science literature.
But a search engine unveiled on 2 November by the non-profit Allen Institute for Artificial Intelligence (AI2) in Seattle, Washington, is working towards providing something different for its users: an understanding of a paper's content. "We're trying to get deep into the papers and be fast and clean and usable," says Oren Etzioni, chief executive officer of AI2.
The free product, called Semantic Scholar, is currently limited to searching about 3 million open-access papers in computer science. But the AI2 team aims to broaden that to other fields within a year, Etzioni says. His team is well financed: AI2 was founded and is backed by Microsoft co-founder Paul Allen, who has given the institute more than US$20 million since 2013.
Semantic Scholar offers a few innovative features, including picking out the most important keywords and phrases from the text without relying on an author or publisher to key them in.
(Score: 2) by VanderDecken on Tuesday November 03 2015, @09:57PM
Maybe a transient problem or something like a script blocker? I did a couple of CS-related searches and was able to get the full pdf for any reference I tried. (I checked for DAGs and cache coherency)
The two most common elements in the universe are hydrogen and stupidity.