Classification > more     When trying to visualize the proximity structure of a high dimensional pattern, one frequently has to choose between clustering into a hierarchical tree, or projecting the pattern in two or three dimensions. Conventional wisdom considers that multi-dimensional scaling (projection) is good at representing the big picture, whereas hierarchical clustering handles local details more faithfully. Ideally, one would want a low-dimensional configuration rendering both the global and local properties; such that, for example, if one drew between the final points a hierarchical tree obtained from the original data, this tree would appear simple and related branches would stay next to each other. Our research adapts existing scaling algorithms to create such tree-friendly configurations. More           Cultural Biases on the Web > more     In conjunction with France Telecom an experiment was undertaken to look for differences in web browsing strategies between French and Americans. More