License: Creative Commons Attribution 4.0 PDF - Published Version (1MB) |
- URN to cite this document:
- urn:nbn:de:bvb:355-epub-540577
- DOI to cite this document:
- 10.5283/epub.54057
Abstract
Recent advancements in natural language processing (NLP) methods have significantly improved their performance. However, more complex NLP models are more difficult to interpret and computationally expensive. Therefore, we propose an approach to dictionary creation that carefully balances the trade-off between complexity and interpretability. This approach combines a deep neural network ...
Owner only: item control page