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A neuro-advertising property video recommendation system

机译：神经广告属性视频推荐系统

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摘要

Many factors influence the identification of the best real estate alternatives, such as supply and demand and the social, cultural, psychological and personal factors affecting buyer behavior and the emotional state of a buyer. What are the most effective ways of choosing a property, when the selection is so vast and complex? An aid is developed here to accomplish this, based on a new advertising format, an iterative method and the NEuro-Advertising Property Video Recommendation System (NEAR). A known methodology involves behavioral operational research and the emotions involved in decision-making. Three advanced research contributions are unique to the proposed method and NEAR, in contrast to innovative behavioral operational research. Firstly, data are compiled for a neuro decision matrix, based on housing attributes and the valence, arousal, emotional state and physiological parameters of a potential real estate buyer. Secondly, the performance of a multiple criteria neuroanalysis occurs as well as the selection of the most personalized and effective video clip ad variants drawn from many alternatives. Finally, NEAR is found to present the most effective video clips ads for real estate buyers for as long a period as possible, according to Multiple Resource Theory.
机译：许多因素会影响最佳房地产替代方案的确定，例如供需以及影响买方行为和买方情绪状态的社会，文化，心理和个人因素。当选择如此庞大而复杂时，最有效的选择方式是什么？基于新的广告格式，迭代方法和NEuro广告属性视频推荐系统（NEAR），在此开发了一种辅助工具来实现此目的。已知的方法涉及行为运营研究和决策中涉及的情绪。与创新的行为运筹学相比，三项先进的研究成果是该方法和NEAR独有的。首先，基于房屋属性以及潜在房地产购买者的价，唤醒，情绪状态和生理参数，为神经决策矩阵编译数据。其次，进行多标准神经分析以及从许多替代方案中选择最个性化和最有效的视频剪辑广告变体。最后，根据多种资源理论，发现NEAR可以在尽可能长的时间内为房地产购买者展示最有效的视频剪辑广告。

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