available through the Bing Maps Web site ( http://vis.berkeley.edu/DestMap) (see Figure 6).

We applied a similar approach to automatically generating maps for tourists visiting a new city. 8 Prior work on mental representations of cities16 showed that people consider five main elements: landmarks, paths, districts, nodes, and edges. However, a map with every instance of such elements would be cluttered with excessive detail. The most-effective tourist maps include only those elements that are semantically meaningful (such as the home of a well-known writer), visually distinctive (such as an oddly shaped or colored building), or placed in a structurally important location (such as a building at a prominent intersection). 22 After choosing the elements to include in the map, mapmakers usually apply a variety of cartographic-generalization techniques, including simplification, displacement, deformation, and selection. Cognitive psychologists and cartographers studying the cognition of maps have shown such generalizations improve clarity because they emphasize the most important map elements while preserving spatial relationships between these elements. 17

Our tourist-map-design system is
based on these design principles. In-
put consists of a geometric model of a
city, including streets, bodies of water,
parks, and buildings (with textures).
The system automatically determines
the importance of map elements us-
ing top-down Web-based information-
extraction techniques to compute
semantic importance and bottom-up
vision-based image/geometry analy-
sis to compute visual and structural
importance. It then generates a map
that emphasizes the most important
map elements, using a combination
of multi-perspective rendering and
cartographic generalization to high-
light the important landmarks, paths,
districts, nodes, and edges while de-
emphasizing less-important elements
(see Figure 7).

Comprehension. Participants use the ranked visualizations, and we test for improvements in learning, comprehension, and decision making. In the assembly-instructions project, yet another set of participants assembled the TV stand, this time using the instructions rated in the preference phase. Tests showed the highly rated instructions were easier to use and follow; participants spent less time assembling the TV stand and made fewer errors.

Figure 8. We asked subjects to assemble a tV stand and then create instructions for a novice explaining how to assemble it (left, middle). analyzing hand-drawn instructions, we found that diagrammatic, step-by-step instructions using guidelines and arrows to indicate the actions required for assembly and providing good visibility for the attached parts are easiest to use and follow. our system automatically generates assembly instructions (right) based on these principles.