Optimizing impression counts for outdoor advertising

Abstract

In this paper we propose and study the problem of optimizing the influence of outdoor advertising (ad) when impression counts are taken into consideration. Given a database U of billboards, each of which has a location and a non-uniform cost, a trajectory database T and a budget B, it aims to find a set of billboards that has the maximum influence under the budget. In line with the advertising consumer behavior studies, we adopt the logistic function to take into account the impression counts of an ad (placed at different billboards) to a user trajectory when defining the influence measurement. However, this poses two challenges: (1) our problem is NP-hard to approximate within a factor of O..