Knowing the unknown: Visualising consumption blind-spots in recommender systems
Authors: Tintarev, N., Rostami, S. and Smyth, B.
Journal: Proceedings of the ACM Symposium on Applied Computing
Pages: 1396-1399
ISBN: 9781450351911
DOI: 10.1145/3167132.3167419
Abstract:In this paper we consider how to help users to better understand their consumption profiles by examining two approaches to visualising user profiles - chord diagrams, and bar charts - aimed at revealing to users those regions of the recommendation space that are unknown to them, i.e. blind-spots. Both visualisations do this by connecting profile preferences with a filtered recommendation space. We compare and contrast the two visualisations in a live user study (n = 70). The results suggest that, although users can understand both visualisations, chord diagrams are particularly effective in helping users to identify blind-spots, while simpler bar charts are better for conveying what was already known in a profile. Evaluating the understandability of blind-spot visualizations is a first step toward using visual explanations to help address a criticism of recommender systems: that personalising information creates filter bubbles.
https://eprints.bournemouth.ac.uk/30801/
Source: Scopus
Knowing the Unknown: Visualising Consumption Blind-Spots in Recommender Systems
Authors: Tintarev, N., Rostami, S. and Smyth, B.
Journal: 33RD ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING
Pages: 1396-1399
DOI: 10.1145/3167132.3167419
https://eprints.bournemouth.ac.uk/30801/
Source: Web of Science (Lite)
Knowing the unknown: visualising consumption blind-spots in recommender system
Authors: Nava, T., Rostami, S. and Smyth, B.
Conference: Symposium on Applied Computing (SAC)
Dates: 9-13 April 2018
https://eprints.bournemouth.ac.uk/30801/
Source: Manual
Knowing the unknown: visualising consumption blind-spots in recommender system
Authors: Nava, T., Rostami, S. and Smyth, B.
Conference: SAC 2018 The 33rd ACM/SIGAPP Symposium On Applied Computing
Publisher: ACM SAC 2018
Abstract:In this paper we consider how to help users to better understand their consumption profiles by examining two approaches to visualising user profiles – chord diagrams, and bar charts – aimed at revealing to users those regions of the recommendation space that are unknown to them, i.e. blind-spots. Both visualisations do this by connecting profile preferences with a filtered recommendation space. We compare and contrast the two visualisations in a live user study (n = 70). The results suggest that, although users can understand both visualisations, chord diagrams are particularly effective in helping users to identify blind-spots, while simpler bar charts are better for conveying what was already known in a profile.
Evaluating the understandability of blind-spot visualizations is a first step toward using visual explanations to help address a criticism of recommender systems: that personalising information creates filter bubbles.
https://eprints.bournemouth.ac.uk/30801/
https://www.sigapp.org/sac/sac2018/
Source: BURO EPrints