首页> 外文会议>International Conference on Rough Sets and Current Trends in Computing(RSCTC 2006); 20061106-08; Kobe(JP) >A Proposal for Comparison of Impression Evaluation Data Among Individuals by Using Clustering Method Based on Distributed Structure of Data
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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比较个人印象评估数据的建议

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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,公司经常向消费者进行问卷调查,以掌握他们对产品的印象。分析从消费者那里获得的评估数据,使我们能够掌握市场趋势并发现问题和/或做出对产品开发有用的假设。语义差异(SD)方法是量化人类对对象印象的最有用的方法之一。这项研究的目的是开发一种可视化数据中各个特征的方法。本文提出了一种基于正交前验分析(OPA)的聚类方法。所提出的方法可以将SD评估数据的分布结构相似的主题聚类。通过这种方法的分析导致发现多数/少数群体和/或具有独特特征的群体。另外,它使我们能够通过比较聚类中心和/或变换矩阵来分析聚类和/或主题之间的对象和印象词的相似性/差异。本文将提出的方法应用于实际的SD评估数据。结果表明,该方法可以研究每个组中对象之间的相似关系,并比较同一聚类中对象之间用于评价对象的印象词的相似性/差异性。

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