A recommendation dashboard utilising micro-filter visualisations: An evaluation and investigation of applicability on mobile devices

Abstract

One classic issue associated with being a researcher nowadays is the multitude and magnitude of search results for a given topic. Recommender systems can help to fix this problem by directing users to the resources most relevant to their specific research focus. However, sets of automatically generated recommendations are likely to contain irrelevant resources, making user interfaces that provide effective filtering mechanisms necessary. This problem is exacerbated when users resume a previously interrupted research task, or when different users attempt to tackle one extensive list of results, as confusion as to what resources should be consulted can be overwhelming. The presented recommendation dashboard uses micro-visualisations to display the state of multiple filters in a data type-specific manner. This paper describes the design and geometry of micro-visualisations and presents results from an evaluation of their readability and memorability in the context of exploring recommendation results. Based on that, this paper also proposes applying micro-visualisations for extending the use of a desktop-based dashboard to the needs of small-screen, mobile multi-touch devices, such as smartphones. A small-scale heuristic evaluation was conducted using a first prototype implementation.