Uber Technologies, Inc.
Anticipating user dissatisfaction via machine learning

Abstract:

A server of a transportation network determines characteristics of trips provided to users, as well as the usage of the services by users. Using the determined characteristics, the server trains a model that, for a given set of trips for a user, estimates a degree of likely user dissatisfaction with the trips. Based on the estimated degree of user dissatisfaction, the system can estimate user dissatisfaction in real time, directly after completion of a trip, and can take remedial actions should the user be estimated to be likely dissatisfied.