Healthcare knowledge provider BMJ and UNSILO have announced 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.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.
