Projects per year
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.
|Title of host publication||RecSys '20: Fourteenth ACM Conference on Recommender Systems|
|Publisher||Association for Computing Machinery|
|Number of pages||6|
|Publication status||Published - 22 Sep 2020|
|MoE publication type||A4 Article in a conference publication|
|Event||conference; 2020-09-22; 2020-09-26 - Fourteenth ACM Conference on Recommender Systems|
Duration: 22 Sep 2020 → 26 Sep 2020
|Conference||conference; 2020-09-22; 2020-09-26|
|Period||22/09/20 → 26/09/20|
- conversational recommender systems
- critiquing recommender systems
- information exploration tool
- interactive recommendation
- recommender systems
- related item recommendations
- user control
- user interfaces
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- 1 Finished
LibDat: Towards a More Advanced Loaning and Reading Culture. A Study, Based on Digital Material, of Contemporary Finnish Loaning and Reading Habits
Neovius, M., Kotkov, D., Maslov, A. & Satyal, U. R.
01/09/17 → 30/08/21