Maximizing the Utility in Location-Based Mobile Advertising

Nowadays, the locations and contexts of users are easily accessed by mobile advertising brokers, and the brokers can send customers related location-based advertisement. In this paper, we consider a location-based advertising problem, namely maximum utility advertisement assignment (MUAA) problem, with the estimation of the interests of customers and the contexts of the vendors, we want to maximize the overall utility of ads by determining the ads sent to each customer subject to the constraints of the capacities of customers, the distance ranges and the budgets of vendors. We prove that the MUAA problem is NP-hard and intractable. Thus, we propose one offline approach, namely the reconciliation approach, which has an approximation ratio of (1-e)⋅θ, where θ = min(a_1\n^c_1, a_2 n^c_2,..., a_m n^c_m), and n^c_i is the larger value between the number of valid vendors and the capacity a_i of customer u_i. Experiments on real data sets confirm the efficiency and effectiveness of our proposed approach.