Theme: Scholarly Knowledge MiningTheme: Scholarly Knowledge Mining Scholarly Knowledge Mining
Theme: Digital HumanitiesTheme: Digital Humanities Digital Humanities
Theme: Data ScienceTheme: Data Science Data Science
Theme: Smart Cities and RoboticsTheme: Smart Cities and Robotics Smart Cities and Robotics

Finalists at DataIQ 2020 Awards

2nd October 2020

The Smart Topic Miner, which is an innovative state-of-the-art AI application for automating editorial processes at Springer Nature and improving access to scientific knowledge, has been shortlisted for the “Most Innovative use of AI” DataIQ 2020 Awards. Smart Topic Miner analyses scientific publications in Computer Science and classifies them with very high accuracy in terms of a catalogue of 15,000 research topics. The automation of this complex task has produced both a 75% cost reduction and a dramatic improvement in metadata quality. As a result of the latter, downloads in Computer Science from the Springer Nature portal have increased by almost 10 million units, as search engines can now identify the relevant scientific content with much higher accuracy, thus benefitting readers of scientific literature all over the world.

At the SKM3 team, we are very honoured to receive such great recognition, as it further proves the impact of our work and specifically the Smart Topic Miner.

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