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Construction of customers’ emotion model in the bespoke tailoring using evaluation grid method

机译:利用评估网格法在定制中定制顾客情感模型

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To realize a recommendation system that combines the benefits of human recommendation (experts in the field, e.g., salesclerks) and computer recommendation (recommendation algorithms, such as those in e-commerce), we constructed an emotion model that appropriately represents customers' emotions during a human recommendation process. As a typical scene of a recommendation by a human, we focused on bespoke tailoring in which a customer interacts with a tailor. First, we extracted emotions evoked in the scene using the evaluation grid method. After that, we constructed an emotion model by determining the extracted emotions' positions on the core affect model. As a result, we constructed an emotion model that appropriately expressed the emotions evoked in the recommendation process. In addition, we found that unique emotions such as troubled and expected are evoked in the recommendation by a human.
机译:为了实现一个结合了人类推荐(该领域的专家,例如销售员)和计算机推荐(推荐算法,例如电子商务中的推荐算法)的好处的推荐系统,我们构建了一个情感模型,可以恰当地表示客户在此过程中的情感人工推荐过程。作为人类推荐的典型场景,我们专注于定制裁缝,在该裁缝中,客户与裁缝进行交互。首先,我们使用评估网格方法提取场景中引起的情绪。之后,我们通过确定提取的情绪在核心情感模型上的位置来构建情绪模型。结果,我们构建了一个情感模型,可以恰当地表达推荐过程中引起的情感。此外,我们发现人的推荐中会引起诸如麻烦和期望之类的独特情绪。

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