Miletic, Marko; Sariyar, Murat (2022). Explaining Contextualized Word Embeddings in Biomedical Research – A Qualitative Investigation Studies in Health Technology and Informatics, 295, pp. 289-292. IOS Press 10.3233/SHTI220719
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Contextualized word embeddings proved to be highly successful quantitative representations of words that allow to efficiently solve various tasks such as clinical entity normalization in unstructured texts. In this paper, we investigate how the Saussurean sign theory can be used as a qualitative explainable AI method for word embeddings. Our assumption is that the main goal of XAI is to produce confidence and/or trust, which can be gained through quantitative as well as quantitative approaches. One important result is related to the fact that the differential structure of language as explained by Saussure corresponds to the possibility of adding and subtracting word embeddings. On the other hand, these mathematical structures provide insights into the inner workings of natural language.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
School of Engineering and Computer Science > Institut für Medizininformatik I4MI School of Engineering and Computer Science |
Name: |
Miletic, Marko and Sariyar, Murat |
Subjects: |
Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
ISSN: |
1879-8365 |
ISBN: |
9781643682907 |
Series: |
Studies in Health Technology and Informatics |
Publisher: |
IOS Press |
Language: |
English |
Submitter: |
Murat Sariyar |
Date Deposited: |
20 Dec 2022 15:33 |
Last Modified: |
15 Jan 2024 15:26 |
Publisher DOI: |
10.3233/SHTI220719 |
ARBOR DOI: |
10.24451/arbor.18476 |
URI: |
https://arbor.bfh.ch/id/eprint/18476 |
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