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University of Regensburg @ SwissText 2021 SEPP-NLG: Adding Sentence Structure to Unpunctuated Text
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TwistBytes : hierarchical classification at GermEval 2019 : walking the fine line (of recall and precision) ...
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Benites, Fernando. - : German Society for Computational Linguistics & Language Technology, 2019
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Abstract:
We present here our approach to the GermEval 2019 Task 1 - Shared Task on hierarchical classification of German blurbs. We achieved the first place in the hierarchical subtask B and second place on the root node, flat classification subtask A. In subtask A, we applied a simple multi-feature TF-IDF extraction method using different n-gram range and stopword removal, on each feature extraction module. The classifier on top was a standard linear SVM. For the hierarchical classification, we used a local approach, which was more lightweighted but was similar to the one used in subtask A. The key point of our approach was the application of a post-processing to cope with the multi-label aspect of the task, increasing the recall but not surpassing the precision measure score. ...
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Keyword:
410.285 Computerlinguistik
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URL: https://digitalcollection.zhaw.ch/handle/11475/18848 https://dx.doi.org/10.21256/zhaw-18848
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The reader's feeling and text-based emotions : the relationship between subjective self-reports, lexical ratings, and sentiment analysis ...
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spMMMP at GermEval 2018 Shared Task: Classification of Offensive Content in Tweets using Convolutional Neural Networks and Gated Recurrent Units
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In: http://hw.oeaw.ac.at/8435-5 (2018)
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