We present a method by which to convert a large corpus of website traffic data into
interactive and practical taste graph visualizations. The website traffic data lists individual
visitors' level of interest in specific pages across the website; it is a tripartite list consisting of
anonymized visitor ID, webpage ID, and a score that quantifies interest level. Taste graph
visualizations reveal psychological profiles by revealing connections between consumer
tastes; for example, an individual with a taste for A may be also have a taste for B. We …