Another Semantic Search Play
November 6, 2015
The University of Washington has been search central for a number of years. Some interesting methods have emerged. From Jeff Dean to Alon Halevy, the UW crowd has been having an impact.
Now another search engine with ties to UW wants to make waves with a semantic search engine. Navigate to “Artificial-Intelligence Institute Launches Free Science Search Engine.” The wizard behind the system is Dr. Oren Etzioni. The money comes from Paul Allen, a co founder of Microsoft.
Dr. Etzioni has been tending vines in the search vineyard for many years. His semantic approach is described this way:
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.
Sound familiar: Understanding what a sci-tech paper means?
According to the write up:
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. “It’s surprisingly difficult for a system to do this,” says Etzioni. The search engine uses similar ‘machine reading’ techniques to determine which papers are overviews of a topic. The system can also identify which of a paper’s cited references were truly influential, rather than being included incidentally for background or as a comparison.
Does anyone remember Gene Garfield? I did not think so. There is a nod to Expert System, an outfit which has been slogging semantic technology in an often baffling suite of software since 1989. Yep, that works out to more than a quarter of a century.) Hey, few doubt that semantic hoohah has been a go to buzzword for decades.
There are references to the Microsoft specialist search and some general hand waving. The fact that different search systems must be used for different types of content should raise some questions about the “tuning” required to deliver what the vendor can describe as relevant results. Does anyone remember what Gene Garfield said when he accepted the lifetime achievement award in online? Right, did not think so. The gist was that citation analysis worked. Additional bells and whistles could be helpful. But humans referencing substantive sci-tech antecedents was a very useful indicator of the importance of a paper.
I interpreted Dr. Garfield’s comment as suggesting that semantics could add value if the computational time and costs could be constrained. But in an era of proliferating sci-tech publications, bells and whistles were like chrome trim on a 59 Oldsmobile 98. Lots of flash. Little substance.
My view is that Paul Allen dabbled in semantics with Evri. How did that work out? Ask someone from the Washington Post who was involved with the system.
Worth testing the system in comparative searches against commercial databases like Compendex, ChemAbs, and similar high value commercial databases.
Stephen E Arnold, November 5, 2015
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Another Semantic Search Play : Stephen E. Arnold @ Beyond Search