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Developing Forecasting Model in Thailand Fashion Market Based on Statistical Analysis and Content-Based Image Retrieval

机译:基于统计分析和基于内容的图像检索开发泰国时装市场预测模型

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摘要

Traditional trend forecasting process in Thailand fashion industry was challenged by a fast fashion. In this paper, the Content-Based Image Retrieval (CBIR) technique is utilized for retrieval of a fashion trendsetter in fast fashion influence. Firstly, six fashion theories were implemented as 12 variables affecting the trendsetter. Cluster analysis, and factor analysis approach were used to find out the source of a fashion trendsetter as well. Cluster analysis separated all samples into three groups with different fashion ways. Moreover, factor analysis technique grouped all variables into three important factors. From such techniques, Internet media clearly is the best source of a fashion trendsetter. In the authors 'model, traditional forecasting sources were added up with a fast fashion influence from CBIR. Then, the CBIR was evaluated in terms of efficiency compared with a real fashion expert in the Thai fashion industry. From statistical test, spatial color distribution yields high efficiency in selecting similar fashion style as a fashion expert.
机译:泰国时装业的传统趋势预测过程受到快速时装的挑战。在本文中,基于内容的图像检索(CBIR)技术被用于以快速的时尚影响力检索时尚潮流引领者。首先,将六种时尚理论作为影响潮流引领者的12个变量加以实施。聚类分析和因素分析方法也被用来找出时尚潮流引领者的来源。聚类分析将所有样品分为三种不同方式的组。此外,因素分析技术将所有变量分为三个重要因素。通过这种技术,互联网媒体显然是时尚潮流引领者的最佳来源。在作者的模型中,传统的预测来源加上了CBIR的快速影响。然后,与泰国时装业的一位真正的时尚专家相比,对CBIR进行了效率评估。从统计测试来看,空间色彩分布在选择与时尚专家相似的时尚风格时具有很高的效率。

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