Name
Abstract | ||
|---|---|---|
Explanations are a key concept of public-service remits. For their linear program, public broadcasters regularly report on how they reflect diversity and balance in their program. For personalized public media, however, explanations must be different, as not one, but thousands of individual playouts have to be explained. We propose an approach how to design explanations for content-based radio recommendations based on word embedding approaches and evaluate the acceptance of our explanations with interviews of test listeners. As a result, we reveal a paradox-test listeners appreciate to have explanations, but at the same time do not intend to use the explanation feature often.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3386392.3399306 | UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization
Genoa
Italy
July, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-7950-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Hirschmeier | 1 | 0 | 1.35 |
| Detlef Schoder | 2 | 350 | 46.46 |