Sammanfattning
Related item recommendations have a long history in recommender systems, but they tend to be a static list of similar items with respect to a target item of interest without any support of user control. In this paper, we propose ClusterExplorer, a novel approach for enabling user control over related recommendations. The approach allows users to explore the latent space of user-item interactions through controlling related recommendations. We evaluated ClusterExplorer in the book domain with 42 participants recruited in a public library and found that our approach has higher user satisfaction of browsing items and is more helpful in finding interesting items compared to traditional related item recommendations.
Originalspråk | Engelska |
---|---|
Titel på gästpublikation | RecSys '20: Fourteenth ACM Conference on Recommender Systems |
Förlag | Association for Computing Machinery |
Sidor | 432–437 |
Antal sidor | 6 |
ISBN (elektroniskt) | 9781450375832 |
ISBN (tryckt) | 9781450375832 |
DOI | |
Status | Publicerad - 22 sep 2020 |
MoE-publikationstyp | A4 Artikel i en konferenspublikation |
Evenemang | conference; 2020-09-22; 2020-09-26 - Fourteenth ACM Conference on Recommender Systems Varaktighet: 22 sep 2020 → 26 sep 2020 |
Konferens
Konferens | conference; 2020-09-22; 2020-09-26 |
---|---|
Period | 22/09/20 → 26/09/20 |
Nyckelord
- conversational recommender systems
- critiquing recommender systems
- information exploration tool
- interactive recommendation
- recommender systems
- related item recommendations
- user control
- user interfaces