Most recommender systems present recommended products in lists
to the user. By doing so, much information is lost about the
mutual similarity between recommended products. We propose to
represent the mutual similarities of the recommended products
in a two dimensional space, where similar products are located close to each
other and dissimilar products far apart. As a dissimilarity measure we use an
adaptation of Gower's similarity coefficient based on the attributes of a product. Two
recommender systems are developed that use this approach.
The first, the graphical recommender system, uses a description
given by the user in terms of product attributes of an
ideal product. The second system, the graphical shopping
interface, allows the user to navigate towards the product he
wants. We show a prototype application of both systems to
MP3-players