L Hughes-Noehrer
Biographic Data
| ID | 3534743 |
|---|---|
| NAME | L Hughes-Noehrer |
| GIVEN NAMES | L |
| FAMILY NAME | Hughes-Noehrer |
| SIGNATURE | HUGHES-NOEHRER L |
| AFFILIATIONS | The University of Manchester |
| ORCID | 0000-0002-9167-0397 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Recommending art online
Museum online collections now contain millions of objects, making developing tools for supporting users in navigating these a priority. We present a user-centric study of a recommendation system created to browse Art UK’s digital collection according to personal preference. Three forms of recommendations were explored: image-only, metadata-only, and a combination of the two. Recommendations were evaluated against a baseline of artworks chosen at …
The impact of Covid-19 on digital data practices in museums and art galleries in the UK and the US
The first quarter of 2020 heralded the beginning of an uncertain future for museums and galleries as the COVID-19 pandemic hit and the only means to stay ‘open’ was to turn towards the digital. In this paper, we investigate how the physical closure of museum buildings due to lockdown restrictions caused shockwaves within their digital strategies and changed their data practices potentially for good. We review the impact of COVID-19 on the museum …
No prominent works on this page.
The impact of Covid-19 on digital data practices in museums and art galleries in the UK and the US
The first quarter of 2020 heralded the beginning of an uncertain future for museums and galleries as the COVID-19 pandemic hit and the only means to stay ‘open’ was to turn towards the digital. In this paper, we investigate how the physical closure of museum buildings due to lockdown restrictions caused shockwaves within their digital strategies and changed their data practices potentially for good. We review the impact of COVID-19 on the museum …
Recommending art online
Museum online collections now contain millions of objects, making developing tools for supporting users in navigating these a priority. We present a user-centric study of a recommendation system created to browse Art UK’s digital collection according to personal preference. Three forms of recommendations were explored: image-only, metadata-only, and a combination of the two. Recommendations were evaluated against a baseline of artworks chosen at …
Aesthetic Perception and Analysis (2 works) · Museums and Cultural Heritage (2 works) · Best practice (1 work) · Computer Science (1 work) · Data science (1 work) · Desk (1 work) · Digital media (1 work) · Geography (1 work) · Human–computer interaction (1 work) · Pandemic (1 work)