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ORCID15th KONVENS 2019: Erlangen, Germany
- Proceedings of the 15th Conference on Natural Language Processing, KONVENS 2019, Erlangen, Germany, October 9-11, 2019. 2019
KONVENS 2019 Papers
Long Papers
- Kai Labusch, Clemens Neudecker, David Zellhöfer:
BERT for Named Entity Recognition in Contemporary and Historic German. - Michael Wiegand, Margarita Chikobava, Josef Ruppenhofer:
A Supervised Learning Approach for the Extraction of Sources and Targets from German Text. - Michael Wiegand, Leonie Lapp, Josef Ruppenhofer:
A Descriptive Analysis of a German Corpus Annotated with Opinion Sources and Targets. - Edit Szügyi, Sören Etler, Andrew Beaton, Manfred Stede:
Automated Assessment of Language Proficiency on German Data. - Christian Wartena
:
A Probabilistic Morphology Model for German Lemmatization. - Veronika Hintzen, Alexander Fraser:
To Act Or Not To Act - Annotating and Classifying Email Regarding Necessary Action. - Anna Hätty, Ulrich Heid, Anna Moskvina, Julia Bettinger, Michael Dorna, Sabine Schulte im Walde:
AkkuBohrHammer vs. AkkuBohrhammer: Experiments towards the Evaluation of Compound Splitting Tools for General Language and Specific Domains. - Dirk Johannßen, Chris Biemann:
Neural classification with attention assessment of the implicit-association test OMT and prediction of subsequent academic success. - Deniz Cevher, Sebastian Zepf, Roman Klinger:
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning. - Maria Skeppstedt, Rafal Rzepka, Kenji Araki, Andreas Kerren:
Visualising and evaluating the effects of combining active learning with word embedding features. - Fabian Karl, Mikko Lauri, Chris Biemann:
Creating Information-maximizing Natural Language Messages Through Image Captioning-Retrieval. - Aashish Agarwal, Torsten Zesch:
German End-to-end Speech Recognition based on DeepSpeech. - Harald Koppen, Ritavan:
Label Propagation of Polarity Lexica on Word Vectors. - Josef Ruppenhofer, Ines Rehbein:
Detecting the boundaries of sentence-like units in spoken German. - Eckhard Bick:
Dependency Trees for Greenlandic. - Ines Reinig, Ines Rehbein:
Metaphor detection for German Poetry. - Gregor Wiedemann, Steffen Remus, Avi Chawla, Chris Biemann:
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings. - Jennifer Fest, Arndt Heilmann, Oliver Hohlfeld, Stella Neumann, Jens Helge Reelfs, Marco Schmitt, Alina Vogelgesang:
Determining Response-generating Contexts on Microblogging Platforms. - Luise Schricker, Manfred Stede, Peer Trilcke:
Extraction and Classification of Speech, Thought, and Writing in German Narrative Texts. - Juri Opitz:
Argumentative Relation Classification as Plausibility Ranking. - Somtochukwu Enendu, Johannes C. Scholtes, Jeroen Smeets, Djoerd Hiemstra, Mariët Theune:
Predicting Semantic Labels of Text Regions in Heterogeneous Document Images. - Katrin Ortmann, Adam Roussel, Stefanie Dipper:
Evaluating Off-the-Shelf NLP Tools for German.
Short Papers
- Gertrud Faaß, Sonja Bosch:
Towards a gold standard corpus for detecting valencies of Zulu verbs. - Roman Schneider:
"Konservenglück in Tiefkühl-Town" - Das Songkorpus als empirische Ressource interdisziplinärer Erforschung deutschsprachiger Poptexte. - Finn Årup Nielsen, Lars Kai Hansen:
Combining embedding methods for a word intrusion task. - Annelen Brunner, Ngoc Duyen Tanja Tu, Lukas Weimer, Fotis Jannidis:
Deep learning for Free Indirect Representation. - Jon Stevens, Brandon Punturo, Derek Chen, Mike Kim, Jacob Zimmer:
Representing document-level semantics of biomedical literature using pre-trained embedding models: Novel assessments. - Stefan Schweter, Sajawel Ahmed:
Deep-EOS: General-Purpose Neural Networks for Sentence Boundary Detection. - Özge Alaçam, Wolfgang Menzel, Tobias Staron:
How Does Visual Complexity Influence Predictive Language Processing in a Situated Context? - Yash Bhalgat, Zhe Liu, Pritam Gundecha, Jalal Mahmud, Amita Misra:
Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation.
Kaleidoscope Abstracts
- Adrien Barbaresi:
Generic Web Content Extraction with Open-Source Software. - Peter M. Fischer, Christian Lang:
Ein Tool zur Visualisierung des Gebrauchs von Schreibvarianten. - Piroska Lendvai, Simone Rebora, Moniek M. Kuijpers:
Identification of Reading Absorption in User-Generated Book Reviews. - Maria Skeppstedt, Magnus Ahltorp, Gunnar Eriksson, Rickard Domeij:
Sketches of a graphical user interface for word alignment annotation. - Michael Richter, Tariq Yousef:
Predicting default and non-default aspectual coding: Impact and density of information features.
GermEval Papers
Task 1
- Steffen Remus, Rami Aly, Chris Biemann:
GermEval 2019 Task 1: Hierarchical Classification of Blurbs. - Franz Bellmann, Lea Bunzel, Christoph Demus, Lisa Fellendorf, Olivia Gräupner, Qiuyi Hu, Tamara Lange, Alica Stuhr, Jian Xi, Dirk Labudde, Michael Spranger:
Multi-Label Classification of Blurbs with SVM Classifier Chains. - Venkatesh Umaashankar, Girish Shanmugam S:
Multi-Label Multi-Class Hierarchical Classification using Convolutional Seq2Seq. - Malte Ostendorff, Peter Bourgonje, Maria Berger, Julián Moreno Schneider, Georg Rehm, Bela Gipp:
Enriching BERT with Knowledge Graph Embeddings for Document Classification. - David S. Batista, Matti Lyra:
COMTRAVO-DS team at GermEval 2019 Task 1 on Hierarchical Classification of Blurbs. - Erdan Genc, Louay Abdelgawad, Viorel Morari, Peter Kluegl:
Convolutional Neural Networks for Classification of German Blurbs. - Fernando Benites:
TwistBytes - Hierarchical Classification at GermEval 2019: walking the fine line (of recall and precision). - Melanie Andresen, Melitta Gillmann, Jowita Grala, Sarah Jablotschkin, Lea Röseler, Eleonore Schmitt, Lena Schnee, Katharina Straka, Michael Vauth, Sandra Kübler, Heike Zinsmeister:
The HUIU Contribution to the GermEval 2019 Shared Task 1. - Raghavan A. K., Venkatesh Umaashankar, Gautham Krishna Gudur:
Label Frequency Transformation for Multi-Label Multi-Class Text Classification. - Kristian Rother, Achim Rettberg:
Logistic Regression and Naive Bayes for Hierarchical Multi-label Classification at GermEval 2019 - Task 1.
Task 2
- Julia Maria Struß, Melanie Siegel, Josef Ruppenhofer, Michael Wiegand, Manfred Klenner:
Overview of GermEval Task 2, 2019 Shared Task on the Identification of Offensive Language. - Michele Corazza, Stefano Menini, Elena Cabrio, Sara Tonelli, Serena Villata:
InriaFBK Drawing Attention to Offensive Language at Germeval2019. - Kristian Rother, Achim Rettberg:
German Hatespeech classification with Naive Bayes and Logistic Regression - hshl at GermEval 2019 - Task 2. - Inna Vogel, Roey Regev:
FraunhoferSIT at GermEval 2019: Can Machines Distinguish Between Offensive Language and Hate Speech? Towards a Fine-Grained Classification. - Florian Schmid, Justine Thielemann, Anna Mantwill, Jian Xi, Dirk Labudde, Michael Spranger:
FoSIL - Offensive language classification of German tweets combining SVMs and deep learning techniques. - Isabell Börner, Midhad Blazevic, Maximilian Komander, Margot Mieskes:
2019 GermEval Shared Task on Offensive Tweet Detection h_da submission. - Johannes Schäfer, Tom De Smedt, Sylvia Jaki:
HAU at the GermEval 2019 Shared Task on the Identification of Offensive Language in Microposts: System Description of Word List, Statistical and Hybrid Approaches. - Andrei Paraschiv, Dumitru-Clementin Cercel:
UPB at GermEval-2019 Task 2: BERT-Based Offensive Language Classification of German Tweets. - Julian Risch, Anke Stoll, Marc Ziegele, Ralf Krestel:
hpiDEDIS at GermEval 2019: Offensive Language Identification using a German BERT model. - Melanie Andresen, Melitta Gillmann, Jowita Grala, Sarah Jablotschkin, Lea Röseler, Eleonore Schmitt, Lena Schnee, Katharina Straka, Michael Vauth, Sandra Kübler, Heike Zinsmeister:
The HUIU Contribution for the GermEval Shared Task 2. - Joaquín Padilla Montani, Peter Schüller:
TUWienKBS19 at GermEval Task 2, 2019: Ensemble Learning for German Offensive Language Detection. - Alistair Plum, Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov:
RGCL at GermEval 2019: Offensive Language Detection with Deep Learning. - Theresa Krumbiegel:
FKIE - Offensive Language Detection on Twitter at GermEval 2019. - Tim Graf, Luca Salini:
bertZH at GermEval 2019: Fine-Grained Classification of German Offensive Language using Fine-Tuned BERT.
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