The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The role of transparency in recommender systems
Abstract
Recommender Systems act as a personalized decision guides, aiding users in decisions on matters related to personal taste. Most previous research on Recommender Systems has focused on the statistical accuracy of the algorithms driving the systems, with little emphasis on interface issues and the user's perspective. The goal of this research was to examine the role of transprency (user understanding of why a particular recommendation was made) in Recommender Systems. To explore this issue, we conducted a user study of five music Recommender Systems. Preliminary results indicate that users like and feel more confident about recommendations that they perceive as transparent.
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Citations
Cites
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Metadata
- Authors
- Sinha, R., & Swearingen, K.
- Venue
- CHI '02 Extended Abstracts on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2002-04-20
- Pages
- 830-831
- OpenAlex
- W2089566520
- Cited by
- 477
- References
- 1
- FWCI
- 4.59
- Type
- conference paper
- Language
- en
- Open access
- closed
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