  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
slot\mbox{-}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 \textsc{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.

Databases