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A knowledge engineering framework for intelligent targeting of online video advertisements

机译:在线视频广告智能定位知识工程框架

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One of the newest and most promising media employed by digital marketing is the distribution of advertising video spots through social media and popular websites. This paper addresses the problem of optimising the effectiveness of such video ads by using intelligent technologies which improve the matching between ads and targeted audience. Multidimensional data analysis methods are applied to discover relations among video ad characteristics, audience characteristics and the resulting effectiveness of the ads, thus extracting knowledge on how certain design features, such as music, scenario and humour may affect aspects of the ad effectiveness. The analysis findings are introduced in a knowledge-based tool so that an inference engine can automatically match selected ads to target audiences for which high prospects of success are predicted. The paper presents the analysis and knowledge engineering methods, as well as results of a small-scale application.
机译:数字营销采用的最新和最有前途的媒体之一是通过社交媒体和流行的网站分发广告视频点。 本文解决了通过使用智能技术优化这些视频广告的有效性的问题,这些技术可以改善广告与目标受众之间的匹配。 多维数据分析方法应用于发现视频广告特征,受众特征和广告所产生的效率之间的关系,从而提取关于某些设计特征的知识,例如音乐,情景和幽默,可能影响广告效能的方面。 分析结果是在基于知识的工具中引入的,因此推理引擎可以自动将所选择的广告与目标受众匹配,以便预测成功的高前景。 本文提出了分析和知识工程方法,以及小规模应用的结果。

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