Deriving Salience Models from Human Route Directions

Abstract

Abstract. We present an approach to derive individual preferences in the use of landmarks for route instructions in a city environment. 1 Each possible landmark that a person can refer to in a given situation is modelled as a feature vector, and the preference (or salience) associated with the landmark can be computed as a weighted sum of these features. The weight vector, representing the person’s personal salience model, is automatically derived from the person’s own route descriptions. Experiments show that the derived salience models can correctly predict the user’s choice of landmark in 69 % of the cases. 1