Multi-Slot Tag Assignment Problem in Billboard Advertisement

TL;DR

This paper addresses the complex problem of optimally assigning tags to billboard slots across regions to maximize influence demand satisfaction, proposing an efficient approximation algorithm validated with real-world data.

Contribution

It introduces the Multi-Slot Tag Assignment Problem, proves its NP-hardness, and develops an effective approximation algorithm with complexity analysis and experimental validation.

Findings

The proposed algorithm outperforms baseline methods in influence demand satisfaction.

The problem is NP-hard, indicating computational complexity.

Experimental results demonstrate the approach's effectiveness and efficiency.

Abstract

Nowadays, billboard advertising has emerged as an effective advertising technique due to higher returns on investment. Given a set of selected slots and tags, how to effectively assign the tags to the slots remains an important question. In this paper, we study the problem of assigning tags to the slots such that the number of tags for which influence demand of each zone is satisfied gets maximized. Formally, we call this problem the Multi-Slot Tag Assignment Problem. The input to the problem is a geographical region partitioned into several zones, a set of selected tags and slots, a trajectory, a billboard database, and the influence demand for every tag for each zone. The task here is to find out the assignment of tags to the slots, such the number of tags for which the zonal influence demand is satisfied is maximized. We show that the problem is NP-hard, and we propose an efficient approximation algorithm to solve this problem. A time and space complexity analysis of the proposed methodology has been done. The proposed methodology has been implemented with real-life datasets, and a number of experiments have been carried out to show the effectiveness and efficiency of the proposed approach. The obtained results have been compared with the baseline methods, and we observe that the proposed approach leads to a number of tags whose zonal influence demand is satisfied.