Klenner, Manfred; Göhring, Anne; Amsler, Michael (2020). Harmonization Sometimes Harms. In: Proceedings of the 5th Swiss Text Analytics Conference (SwissText) & 16th Conference on Natural Language Processing (KONVENS), Winterthur, 23 June 2020 - 25 June 2020, swisstext-and-konvens-2020.
In this paper we argue that harmonization is not the preferred way to produce a gold standard in all cases. Neither does a majority vote based harmonization produce an appropriate gold standard centroid, nor would a mere centroid be a good basis for training a system that reproduces prototypical user reactions given some understanding task. We discuss these claims in the context of sentiment inference.
In this paper we argue that harmonization is not the preferred way to produce a gold standard in all cases. Neither does a majority vote based harmonization produce an appropriate gold standard centroid, nor would a mere centroid be a good basis for training a system that reproduces prototypical user reactions given some understanding task. We discuss these claims in the context of sentiment inference.
| Item Type: | Conference or Workshop Item (Paper), refereed, original work |
|---|---|
| Communities & Collections: | 06 Faculty of Arts > Institute of Computational Linguistics |
| Dewey Decimal Classification: | 000 Computer science, knowledge & systems
410 Linguistics |
| Scopus Subject Areas: | Physical Sciences > General Computer Science |
| Language: | English |
| Event End Date: | 25 June 2020 |
| Deposited On: | 27 Jan 2021 14:49 |
| Last Modified: | 21 Jun 2022 07:14 |
| Publisher: | swisstext-and-konvens-2020 |
| OA Status: | Green |
| Free access at: | Official URL. An embargo period may apply. |
| Official URL: | http://swisstext-and-konvens-2020.org |
Klenner, Manfred