Influential Billboard Slot Selection using Pruned Submodularity Graph
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Billboard Advertisement has emerged as an effective out-of-home advertisement technique and adopted by many commercial houses. In this case, the billboards are owned by some companies and they are provided to the commercial houses slotwise on a payment basis. Now, given the database of billboards along with their slot information which k slots should be chosen to maximize the influence. Formally, we call this problem as the Influential Billboard Slot Selection Problem. In this paper, we pose this problem as a combinatorial optimization problem. Under the `triggering model of influence', the influence function is non-negative, monotone, and submodular. However, as the incremental greedy approach for submodular function maximization does not scale well along with the size of the problem instances, there is a need to develop efficient solution methodologies for this problem.
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