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

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

Start date: 9 April 2018

This data was imported from Scopus:

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

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.

This data was imported from Web of Science (Lite):

Authors: Tintarev, N., Rostami, S., Smyth, B. and Machinery, A.C.


Pages: 1396-1399

DOI: 10.1145/3167132.3167419

The data on this page was last updated at 05:30 on April 13, 2021.