广告牌广告中的多槽位标签分配问题
Multi-Slot Tag Assignment Problem in Billboard Advertisement
AI总结：
针对广告牌广告中标签到槽位的分配问题，本文形式化定义多槽位标签分配问题，证明其NP难，并提出高效近似算法，真实数据集实验验证其优于基线方法。
摘要：
如今，由于更高的投资回报率，广告牌广告已成为一种有效的广告技术。给定一组选定的槽位和标签，如何有效地将标签分配给槽位仍然是一个重要问题。本文研究将标签分配给槽位的问题，以使每个区域的影响需求得到满足的标签数量最大化。形式上，我们将此问题称为多槽位标签分配问题。该问题的输入包括一个被划分为若干区域的地理区域、一组选定的标签和槽位、一条轨迹、一个广告牌数据库，以及每个标签在每个区域的影响需求。这里的任务是找出标签到槽位的分配，使区域影响需求得到满足的标签数量最大化。我们证明该问题是NP难的，并提出一种高效的近似算法来解决该问题。我们对所提方法进行了时间和空间复杂度分析。所提方法已在真实数据集上实现，并开展了大量实验以展示所提方法的有效性和效率。所得结果已与基线方法进行比较，我们观察到所提方法能够带来更多其区域影响需求得到满足的标签。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
