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Tag Archive for: MA-INF

Automatic detection of online insults

Hate speech in the digital sphere has the potential to silence voices and thereby threaten democracy. But hate is not always expressed through swear words online; implicit insults are also ubiquitous. Tracking these down efficiently by technical means, however, is extremely challenging. Michael Wiegand is currently working on the “Recognition of Implicit Insults” in a project funded by the FWF.

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Green Supercomputing: Processing large data volumes more energy-efficiently

Vast quantities of data also signify huge energy consumption. Developers face the task of processing so-called “massive graphs”, i.e. enormous amounts of information and relationships between information nodes, and they have to do this in times when energy is in increasingly short supply. For almost a year, researchers involved in an EU Horizon project have been working on a holistic model to address the ongoing challenges. The goal is, among other things, an energy label for software codes (just like on refrigerators).

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Klaus Schöffmann wins Lifelog Search Challenge 2023

Multimedia researchers around the world are seeking ways to improve the search for content in large image and video pools. Similar to a Grand Slam tournament in tennis, the Video Browser Showdown or the Lifelog Search Challenge is an important competition geared specifically towards these research teams. The world’s best teams compete to see who is the quickest and most accurate at finding what they are looking for. Klaus Schöffmann, associate professor at the Department of Information Technology at the University of Klagenfurt, emerged as the winner of the Lifelog Search Challenge on 12 June 2023.

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Many small software components add up to a single application: Novel methods aim to simplify the detection of side effects caused by changes

Large-scale software applications that combine all their functions in a single component are becoming less common. Instead, we increasingly see applications that are made up of smaller components called microservices. Researchers involved in a newly launched project are working on improving the detection of undesired side effects caused by changes in individual microservices.

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