UNSILO Text Intelligence harnessed to expand Springer Nature’s article metadata

Springer Nature and UNSILO have released a new comprehensive set of article metadata. The new metadata includes keywords for every article, and for articles where no editorial keywords exist, the UNSILO Text Intelligence platform has analysed the full text and selected a set of descriptive Key Concepts.

Traditionally, the content of an academic article has been summarized in three key formats that match the traditional modes of knowledge acquisition and discovery: the abstract, the title, and the editor’s keywords. The importance of these traditional formats is undisputed, but the rise of cross-domain innovation and the evolving needs of researchers place new demands on the ability of these systems to explain the relevance of an article in a particular context.

Springer Nature has partnered with text analytics company UNSILO to develop research tools that understand and build representations of academic articles for these emerging use cases. The key objective is to help researchers spend more time on the most relevant articles, and less time skimming through the ocean of articles that contain the right words, but make no contribution to their research topic.

Henning Schoenenberger, Director of Product Data and Metadata at Springer Nature, said: “Partnerships with leading technology providers are a key component of Springer Nature’s product strategy. We are working closely with UNSILO to meet the evolving needs of researchers. We want to empower people with intelligent tools that provide actionable insights. With the right partnership of man and machine we hope to save the research community time, improve the efficacy of scientific communication and increase the pace of discovery.”

Follow the link below to download the Press Release:

Download SpringerNature Metadata Press Release

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