Biesner, DavidDavidBiesnerBrito, EduardoEduardoBritoHillebrand, Lars PatrickLars PatrickHillebrandSifa, RafetRafetSifa2022-03-142022-03-142020https://publica.fraunhofer.de/handle/publica/409057We propose an alternative quality metric to evaluate automatically generated texts based on an ensemble of different scores, combining simple rule-based metrics with more complex models of very different nature, including ROUGE, tf-idf, neural sentence embeddings, and a matrix factorization method. Our approach achieved one of the top scores on the second German Text Summarization Challenge.en005006629conference paper