A graphical shopping interface based on product attributes

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. Key words: Recommender Systems, Multidimensional Scaling, Similarity, Electronic Commerce, Case-Based Reasoning.

• Type: Journal
• Year: 2008
• Where: DSS
• Authors: Martijn Kagie, Michiel C. van Wezel, Patrick J. F. Groenen
• Keywords: DSS 2008, Most Recommender Systems, Mutual Similarity, Recommender System