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A Proposal for Comparison of Impression Evaluation Data Among Individuals by Using Clustering Method Based on Distributed Structure of Data

机译:基于数据分布式结构的聚类方法,通过使用聚类方法比较个人中的印模评估数据的提议

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In the field of marketing, companies often carry out a questionnaire to consumers for grasping their impressions of products. Analyzing the evaluation data obtained from consumers enables us to grasp the tendency of the market and to find problems and/or to make hypotheses that are useful for the development of products. Semantic Differential (SD) method is one of the most useful methods for quantifying human-impressions to the objects. The purpose of this study is to develop a method for visualization of individual features in data. This paper proposes the clustering method based on Orthogonal Procrustes Analysis (OPA). The proposed method can cluster subjects among whom the distributed structures of the SD evaluation data are similar. The analysis by this method leads to discovery of majority/minority groups and/or groups which have unique features. In addition, it enables us to analyze the similarity/difference of objects and impression words among clusters and/or subjects by comparing the cluster centers and/or transformation matrices. This paper applies the proposed method to an actual SD evaluation data. It shows that this method can investigate the similar relationships among the objects in each group and compare the similarity/difference of impression words used for the evaluation of objects among subjects in the same cluster.
机译:在营销领域,公司经常对消费者进行调查问卷,以掌握其产品的印象。分析从消费者获得的评估数据使我们能够掌握市场的趋势并找到问题和/或制定对产品开发有用的假设。语义差异(SD)方法是对对象量化人印象的最有用方法之一。本研究的目的是开发一种用于可视化数据中各个功能的方法。本文提出了基于正交幼王分析(OPA)的聚类方法。所提出的方法可以群集SD评估数据的分布式结构之间的群集主题。该方法的分析导致多数/少数群体和/或具有独特功能的组的发现。另外,通过比较集群中心和/或转换矩阵,我们使我们能够分析集群和/或受试者之间的对象和印象词的相似性/差异。本文将所提出的方法应用于实际的SD评估数据。它表明该方法可以研究每个组中对象之间的类似关系,并比较用于评估同一群集中的对象之间对象的印象单词的相似性/差异。

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