Knowing the unknown: Visualising consumption blind-spots in recommender systems

Authors: Nava, T., Rostami, S. and Smyth, B.

http://eprints.bournemouth.ac.uk/30801/

Start date: 9 April 2018

This data was imported from Scopus:

Authors: Tintarev, N., Rostami, S. and Smyth, B.

http://eprints.bournemouth.ac.uk/30801/

Journal: Proceedings of the ACM Symposium on Applied Computing

Pages: 1396-1399

ISBN: 9781450351911

DOI: 10.1145/3167132.3167419

© 2018 Authors. 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.

The data on this page was last updated at 04:49 on October 23, 2018.