Text-based annotation of scientific images using Wikimedia categories
- The reuse of scientific raw data is a key demand of Open Science. In the project NOA we foster reuse of scientific images by collecting and uploading them to Wikimedia Commons. In this paper we present a text-based annotation method that proposes Wikipedia categories for open access images. The assigned categories can be used for image retrieval or to upload images to Wikimedia Commons. The annotation basically consists of two phases: extracting salient keywords and mapping these keywords to categories. The results are evaluated on a small record of open access images that were manually annotated.
Download full text files
Akzeptierte Manuskriptversion
Additional Services
Statistics
| Author: | Frieda JosiORCiD, Christian WartenaORCiDGND, Jean CharbonnierORCiD |
|---|---|
| URN: | urn:nbn:de:bsz:960-opus4-12488 |
| DOI: | https://doi.org/10.25968/opus-1248 |
| DOI original: | https://doi.org/10.1007/978-3-319-99133-7_20 |
| ISBN: | 978-3-319-99132-0 |
| ISBN: | 978-3-319-99133-7 |
| Parent Title (English): | Elloumi M. et al. (eds): Database and Expert Systems Applications. DEXA 2018. Communications in Computer and Information Science, vol. 903 |
| Publisher: | Springer |
| Place of publication: | Cham |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of Completion: | 2018 |
| Publishing Institution: | Hochschule Hannover |
| Release Date: | 2018/09/05 |
| Tag: | Scientific image search; Text annotation; Wikipedia categories |
| First Page: | 243 |
| Last Page: | 253 |
| Note: | The final authenticated version is available online at https://doi.org/10.1007/978-3-319-99133-7_20 |
| Link to catalogue: | 1759162078 |
| Institutes: | Fakultät III - Medien, Information und Design |
| DDC classes: | 020 Bibliotheks- und Informationswissenschaft |
| Licence (German): |  Urheberrechtlich geschützt |
