Interactive HPC
Professor (WSR) Oliver Baumann from the Department of Business & Management at SDU tells us how he uses supercomputing for his research and gives us his take on how researchers from social sciences, who are beginning to reach a limit with their own computers, can benefit from Interactive HPC.
In a current project, Baumann collaborates with two American colleagues to study resource allocation in hierarchical organizations…
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A new set of Danish deep learning models for natural language processing (NLP) was trained in UCloud. Danish NLP has in recent years obtained considerable improvements with the addition of multiple new datasets and models. However, at present, there is no coherent framework for applying state-of-the-art models for Danish. We present DaCy: a unified framework for Danish NLP built on SpaCy. DaCy uses efficient multitask models which obtain state-of-the-art performance on named entity recognition, part-of-speech tagging, and dependency parsing.
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One Danish research group can get the unique opportunity to make their metadata machine actionable in a 2 x 1/2 day event – free of charge. The concept is developed by researchers for researchers.
The aim of the M4M WS is to work practically on how to improve your metadata and make them machine-actionable, thus complying with the Findable, Accessible, Interoperable and Reusable (FAIR) principles.
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During the first wave of Covid-19 information decoupling could be observed in the flow of news media content. The corollary of the content alignment within and between news sources experienced by readers (i.e., all news transformed into Corona-news), was that the novelty of news content went down as media focused monotonically on the pandemic event. This all-important Covid-19 news theme turned out to be quite persistent…
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