| Author |
Title |
DOI |
Total Citations |
TC per Year |
Normalized TC |
| Fiorucci et al. (2020) |
Machine Learning for Cultural Heritage: A Survey. Pattern Recognition Letters, |
10.1016/j.patrec.2020.02.017 |
37 |
18.5 |
12.537 |
| Graham et al. (2015) |
Exploring Big Historical Data: The Historian's Macroscope |
10.1142/p981 |
36 |
5.143 |
4.994 |
| van Hooland et al. (2015) |
Exploring Entity Recognition and Disambiguation for Cultural Heritage Collections. |
10.1093/llc/fqt067 |
29 |
4.143 |
4.023 |
| Bruns and Weller (2016) |
Twitter As a First Draft of The Present: And The Challenges Of Preserving It For The Future. |
10.1145/2908131.2908174 |
22 |
3.667 |
7.944 |
| Sabharwal (2015) |
Digital Curation in the Digital Humanities: Preserving and Promoting Archival and Special Collections |
10.1016/C2014-0-02808-0 |
22 |
3.143 |
3.052 |
| Wang (2018) |
Distribution features and intellectual structures of digital humanities. |
10.1108/JD-05-2017-0076 |
19 |
4.75 |
6.135 |
| de Boer et al. (2015) |
DIVE into the event-based browsing of linked historical media. |
10.1016/j.websem.2015.06.003 |
19 |
2.714 |
2.636 |
| Zeng (2019) |
Semantic enrichment for enhancing LAM data and supporting digital humanities. |
10.3145/epi.2019.ene.03 |
18 |
6 |
7.672 |
| Cornia et al. (2020) |
Explaining digital humanities by aligning images and textual descriptions. |
10.1016/j.patrec.2019.11.018 |
15 |
7.5 |
5.083 |
| Grifoni et al. (2018) |
Construction and comparison of 3D multi-source multi-band models for cultural heritage applications. |
10.1016/j.culher.2018.04.014 |
15 |
3.75 |
4.844 |
