Knowing the Unknown

Visualising Consumption Blind-Spots in Recommender System

Conference paper (2018)

Authors

N. Tintarev Web Information Systems - EEMCS
Shahin Rostami Bournemouth University
Barry Smyth University College Dublin
Research Group
Web Information Systems (EEMCS) (TU Delft)
Copyright: © 2018 N. Tintarev, Shahin Rostami, Barry Smyth
DOI: https://doi.org/10.1145/3167132.3167419
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Published Date

2018

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Web Information Systems

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.