# Influential Billboard Slot Selection using Pruned Submodularity Graph

arXiv: https://arxiv.org/abs/2207.06631 · HTML: https://mlsanity.com/paper/2207.06631/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jul 2022.

## Built on by (most cited first, 2 of 2)

- [Towards Regret Free Slot Allocation in Billboard Advertisement](https://mlsanity.com/paper/2401.16464/) (2024)
- [Scalable Submodular Policy Optimization via Pruned Submodularity Graph](https://mlsanity.com/paper/2507.13834/) (2025)

## Abstract (arXiv)

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 slotmbox-wise 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 textscInfluential 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.