Topic models can act as binary classifiers for retrieving news on extreme climate events in German media, with performance varying by hazard type and boosted by keyword probabilities.
In51st Annual Meeting of the Association for Computational Linguistics Pro- ceedings of the Student Research Workshop, pages 67–73, Sofia, Bulgaria
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Retrieving Floods without Floodlights: Topic Models as Binary Classifiers for Extreme Climate Events in German News
Topic models can act as binary classifiers for retrieving news on extreme climate events in German media, with performance varying by hazard type and boosted by keyword probabilities.