Knowing the Unknown: Visualising Consumption Blind-Spots in Recommender Systems
|Title:||Knowing the Unknown: Visualising Consumption Blind-Spots in Recommender Systems||Authors:||Tintarev, Nava
|Permanent link:||http://hdl.handle.net/10197/10165||Date:||13-Apr-2018||Online since:||2019-04-25T11:54:00Z||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||Type of material:||Conference Publication||Publisher:||ACM||Copyright (published version):||2018 the Authors||Keywords:||Visualisation; Recommender Systems; Filter Bubble; Chord Diagram||DOI:||10.1145/3167132.3167419||Other versions:||https://www.sigapp.org/sac/sac2018/||Language:||en||Status of Item:||Peer reviewed||Is part of:||SAC '18 Proceedings of the 33rd Annual ACM Symposium on Applied Computing||Conference Details:||The 33rd Annual ACM/ SIGAPP Symposium on Applied Computing (SAC'18), Pau, France, 9-13 April 2018||ISBN:||978-1-4503-5191-1|
|Appears in Collections:||Insight Research Collection|
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