[New copyright exceptions to text and data mining for non-commercial research have recently come into effect and this is welcome news for UK researchers and research, argues ]{style=“font-family: "arial" , sans-serif;

Stop what you’re doing and go read Cameron Neylon’s blog. Specifically, read his new post, Improving on “Access to Research”. Regular readers of SV-POW! might legitimately complain that my so-called advocacy consists mostly of whining about how rubbish things are.

[ ]{style=“font-family: "arial" , "helvetica" , sans-serif;”} []{style=“font-family: "arial" , "helvetica" , sans-serif;”} [There is a new prototype tool available for browsing on Europe PMC labs: Acromine. Developed and hosted by the National Centre for Textmining, University of Manchester, Acromine suggests expansions of acronyms and presents articles specific to those expansions.

Some quick notes on possibilities for text-mining BHL (in rough order of priority). Any text-mining would have to be robust to OCR errors. I've created a group of OCR-related papers on Mendeley: Skip to content Welcome Enter your email to continue with Mendeley Email Continue Sign in via your organization About Elsevier Terms and conditions Privacy policy Help We use cookies to help provide and enhance our service.

UKPMC Labs is a new component of the UKPMC website, which will showcase novel applications based on UKPMC content. The first application to be featured on the Labs website is EvidenceFinder, an application that surfaces “facts” based on a user’s search terms from full text articles. The user is presented with a list of questions based on the search terms.

Text mining features in databases are an increasingly popular way to extract useful information that could otherwise remain hidden. A new resource has become available to allow researchers to search for particular chemical compounds in biomedical literature. This task is often confounded by multiple names for particular chemicals being used in publications.