The Allen Institute for Artificial Intelligence, also known as AI2, is partnering with Microsoft Research to widen the sphere of scientific search tools by connecting AI2’s Semantic Scholar academic search engine with the Microsoft Academic Graph.
Semantic Scholar is a free online tool makes use of artificial intelligence to maximize the relevance of search results for studies focusing on computer science and biomedicine. Its database takes in more than 40 million academic papers, plus associated blog items, news reports, videos and other resources.
Since its inception in 2015, Semantic Scholar’s user base has grown to more than 2 million monthly users.
Microsoft Academic Graph, meanwhile, charts the networks that knit together more than 200 million academic documents and citations on a wide variety of scientific subjects.
Doug Raymond, Semantic Scholar’s general manager, said the new collaboration is in line with his project’s goal of combating information overload in the scientific community. “This partnership with Microsoft Research relates to our shared interest in this problem,” Raymond told GeekWire.
Kuansan Wang, managing director of Microsoft Research Outreach, said in a news release that he and his colleagues are “thrilled to have this opportunity to work with AI2 on Semantic Scholar.”
“When there are more articles each month describing new scientific discoveries than we have time to read, researchers can use help from AI to comb through the publications and derive insights,” Wang said. “Both AI2 and MSR have world class assets in this area, and by working together we are jointly propelling scientific research and technological advancements to an exciting new level.”
The partnership builds on connections that go back to AI2’s late founder and primary funder, Paul Allen, who also co-founded Microsoft with Bill Gates.
Raymond said the two groups of researchers would collaborate on joint projects to enhance their respective software tools.
For example, Microsoft Academic Graph could be used to help AI2 expand the scope of Semantic Scholar well beyond computer science and biomedicine. “That knowledge graph enables us to provide a more structured, comprehensive, useful representation of science,” Raymond said.
At the same time, the AI-enhanced search strategies that have worked so well for Semantic Scholar could be applied to Microsoft Academic Graph as well.
“We see this as a collaboration on something that will make all science, and all scientists, more impactful,” Raymond said.
He said the users of Semantic Scholar and Microsoft Academic Graph should start seeing the fruits of the collaboration next year. “Stay tuned,” he said.
Correction for 5 a.m. PT Dec. 5: We’ve corrected the spelling of Kuansan Wang’s first name.