Auflistung nach Autor:in "Nadj, Mario"
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- ZeitschriftenartikelFlow-Erfassung am Arbeitsplatz: Aktueller Stand der Forschung und innovative Anwendungsszenarien(Wirtschaftsinformatik & Management: Vol. 9, No. 6, 2017) Rissler, Raphael; Nadj, Mario; Mädche, Alexander; Koppenhagen, Norbert
- KonferenzbeitragAn Interactive Machine Learning System for Image Advertisements(Mensch und Computer 2021 - Tagungsband, 2021) Foerste, Markus; Nadj, Mario; Knaeble, Merlin; Maedche, Alexander; Gehrmann, Leonie; Stahl, FlorianAdvertising is omnipresent in all countries around the world and has a strong influence on consumer behavior. Given that advertisements aim to be memorable, attract attention and convey the intended information in a limited space, it seems striking that previous research in economics and management has mostly neglected the content and style of actual advertisements and their evolution over time. With this in mind, we collected more than one million print advertisements from the English-language weekly news magazine “The Economist” from 1843 to 2014. However, there is a lack of interactive intelligent systems capable of processing such a vast amount of image data and allowing users to automatically and manually add metadata, explore images, find and test assertions, and use machine learning techniques they did not have access to before. Inspired by the research field of interactive machine learning, we propose such a system that enables domain experts like marketing scholars to process and analyze this huge collection of image advertisements.
- ZeitschriftenartikelPower to the Oracle? Design Principles for Interactive Labeling Systems in Machine Learning(KI - Künstliche Intelligenz: Vol. 34, No. 2, 2020) Nadj, Mario; Knaeble, Merlin; Li, Maximilian Xiling; Maedche, AlexanderLabeling is the process of enclosing information to some object. In machine learning it is required as ground truth to leverage the potential of supervised techniques. A key challenge in labeling is that users are not necessarily eager to behave as simple oracles, that is, repeatedly answering questions whether a label is right or wrong. In this respect, scholars acknowledge designing interactivity in labeling systems as a promising area for further improvements. In recent years, a considerable number of articles focusing on interactive labeling systems have been published. However, there is a lack of consolidated principles how to design these systems. In this article, we identify and discuss five design principles for interactive labeling systems based on a literature review and offer a frame for detecting common ground in the implementation of corresponding solutions. With these guidelines, we strive to contribute design knowledge for the increasingly important class of interactive labeling systems.