Papers by Frank Bahrmann
Training a Broad-Coverage German Sentiment Classification Model for Dialog Systems (2020.lrec-1)
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| Challenge: | Existing sentiment data sets are not available for sentiment analysis. |
| Approach: | They propose to combine a German sentiment corpus with existing resources to train a general-purpose German sentiment classification model. |
| Outcome: | The proposed model trains a general-purpose German sentiment classification model . the data set contains 5.4 million labelled samples . |