London and Aarhus, Denmark, January 4, 2019. Today, BMJ and UNSILO announce an agreement by which UNSILO will supply its market-leading concept extraction tools across the whole of BMJ content.
UNSILO applies machine learning and AI tools to identify significant concepts from a corpus of text. These concepts form the basis of a wide range of solutions to publishing workflows, including building subject collections, identifying related articles, finding relevant journals, and many other areas.
Making use of Classify, UNSILO's UI-based tool, BMJ will employ the concept extraction technology to create subject-based collections of journal articles for each of the BMJ journal websites. The use of this automated tool will enable more frequent and fuller collections of articles to be shown and regularly updated.
Uniquely, UNSILO provides a way of combining unsupervised machine learning with configurable human curation, so that in-house staff can adjust the level of automation as they choose. In the future, UNSILO and BMJ will explore further ways AI can automate manual processes and provide deeper insights to support decision making.
Janet O'Flaherty, Journals Publisher, BMJ, commented:
BMJ publishes over 70 journals, and it is a challenge for our editors to create collections of recent articles by hand for each of our journal sites. Using UNSILO, we can update each of these journal home pages more frequently using a largely automated process. We look forward to using UNSILO to further improve our processes as we gain more familiarity with this new technology.
Thomas Laursen, CEO of UNSILO, commented:
UNSILO has been very successful in identifying solutions to workflow challenges in scholarly publishing. We are delighted that BMJ will begin using UNSILO's concept extraction to solve this specific publishing challenge. We look forward to building more tools and to working with a very talented in-house team.
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UNSILO is an artificial intelligence software company that develops advanced tools for text understanding and processing. UNSILO tools deliver dramatic workflow improvements by reducing processing time, while at the same time improving quality and accuracy. The UNSILO Document Enrichment service forms the basis of over 20 separate functional solutions and APIs for publishers, including identifying trending topics as they emerge, automated collections, locating precise relatedness, and now manuscript evaluation, both pre- and post-submission. UNSILO works with world-leading information providers, including Springer Nature and Taylor and Francis, to improve internal publishing processes and external discoverability by authors and researchers. For more information, visit http://unsilo.ai