标题: | 基于智能化电子看板的针对观看人数最大化问题的排程演算法设计 Intelligent Digital Signage-based Advertisement Scheduling Algorithms for Impression Maximization Problem |
作者: | 吴昊东 彭文志 Wu, Hao-Dong Peng, Wen-Chih 资讯科学与工程研究所 |
关键字: | 电子看板;智能;排程演算法;Digital signage;Intelligent;Scheduling algorithms |
公开日期: | 2016 |
摘要: | 近年来,电子看板工业经历了巨大的增长,所以基于电子看板的广告行销问题研究变得越来越热。在这篇论文里,我们对基于电子看板的广告排程定义了一个观看人数最大化的问题。为了帮助排程演算法的设计,我们设计并训练了一个广告模型,用来预测广告的吸引力。我们提出了两大类的广告排程演算法:基于机率的排程演算法,和广告对排程演算法。基于机率的排程演算法帮助我们省下很多时间去决定广告排程的顺序;而广告对排程演算法开创性地先将广告配对,然后把每个广告对当作一个播放单位,再进行排程。当缺乏有吸引力广告时,我们有创造性地主动加入一些有吸引力的内容,用以提高整体广告的观看人数。最后,我们使用真实数据和人造数据进行了一系列实验。实验结果表明我们所提的方法在观看人数最大化的问题上非常有效。 In recent years, the digital signage industry has experienced tremendous growth, so the topic of digital signage-based advertisement scheduling become hotter. In this paper, we study a impression maximization problem for advertisement scheduling on digital signages. We train an AD-model to make our system more intelligent to help our scheduling. We proposed two sets of advertisement scheduling algorithms, probability-based scheduling and AD-Pair scheduling. Our probability-based scheduling algorithms help us to save much time to schedule the playing order. And the AD-Pair scheduling algorithms groundbreakingly bind two Ads together as a playing unit. In the situation that there are not many, even any strong Ads, we creatively add some strong Ads (we call them "Attractions") into the advertisements set given by advertisers, to attract more people to watch the signage. We have conducted comprehensive experiments on synthetic datasets, and the experimental results show that the proposed models are suitable for effective impression maximization in digital signage advertising. |
URI: | http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070356149 http://hdl.handle.net/11536/139661 |
显示于类别: | Thesis |