On-Demand Generalization of Guide Maps with Road Networks and Category-Based Web Search Results

Abstract

The production of strokes according to the perceptual grouping of arcs in a road network provides a good basis for the generalization of road networks, but a large amount of time is required for their creation and selection, and they lack associations with the map objects along them. In this study, we propose a system for generalizing a guide map with road networks and category-based web search results on demand in response to a user request, or a triplet of an area, a size, and a category. The main features of the proposed system are as follows. (1) It constructs a database of strokes and refines the strokes by considering the actual movements of people. It also introduces a data structure called a “fat-stroke,” which combines web search results with the strokes. Pre-construction of the fat-stroke database facilitates the generalization of a guide map on demand to satisfy a user request. (2) It ranks the strokes in order of significance in a guide map according to the web search results combined with the strokes, as well as their length. (3) It determines the number of strokes that need to be drawn on a map based on the map scale and the proportion of road area relative to the whole area in the map. We developed a prototype of the proposed system and a preliminary evaluation demonstrated that pre-construction of the fat-stroke database reduced the response time for guide map generalization to less than 1 s, and thus it can be applied to web map services.