Putting Recommendations on the Map -- Visualizing Clusters and Relations

TL;DR

This paper introduces a novel visualization method using geographic maps to better illustrate clusters and relationships among recommendations, improving user understanding of similarities in TV shows and music selections.

Contribution

It proposes using geographic map layouts for recommendation visualization, enhancing the depiction of clusters and neighborhoods over traditional 2D embeddings.

Findings

Maps improve visualization of clusters and neighborhoods.

Enhanced understanding of recommendation relationships.

Effective for TV shows and music data.

Abstract

For users, recommendations can sometimes seem odd or counterintuitive. Visualizing recommendations can remove some of this mystery, showing how a recommendation is grouped with other choices. A drawing can also lead a user's eye to other options. Traditional 2D-embeddings of points can be used to create a basic layout, but these methods, by themselves, do not illustrate clusters and neighborhoods very well. In this paper, we propose the use of geographic maps to enhance the definition of clusters and neighborhoods, and consider the effectiveness of this approach in visualizing similarities and recommendations arising from TV shows and music selections. All the maps referenced in this paper can be found in http://www.research.att.com/~volinsky/maps