Extracting Landmarks with Data Mining Methods

The navigation task is a very demanding application for mobile users. The algorithms of present software solutions are based on the established methods of car navigation systems and thus exhibit some inherent disadvantages: findings in spatial cognition research have shown that human users need landmarks for an easy and successful wayfinding. Typically, however, an object is not a landmark per se, but can be one relative to its environment. Unfortunately, these objects are not part of route guidance information systems at the moment. Therefore, it is an aim of research to make landmarks for routing instructions available. In this paper we focus on a method to automatically derive landmarks from existing spatial databases. Here a new approach is presented to investigate existing spatial databases and try to extract landmarks automatically by use of a knowledge discovery process and data mining methods. In this paper two different algorithms, the classification method ID3 and the clustering procedure Cobweb, are investigated, whether they are suitable for discovering landmarks.