Neural modelling of ranking data with an application to stated preference data

CATHERINE KRIER, MICHEL MOUCHART & OULHAJ, ABDERRAHIM; DTU, Nuffield Department Of Clinical Medecine - University Of Oxford
Although neural networks are commonly encountered to solve classification problems, ranking data present specificities which require adapting the model. Based on a latent utility function defined on the characteristics of the objects to be ranked, the approach suggested in this paper leads to a perceptron-based algorithm for a highly non linear model. Data on stated preferences obtained through a survey by face-to-face interviews, in the field of freight transport, are used to illustrate the method....