利用文本挖掘技术进行美发关键词衍生分析

So-Hyeon Kim, Jeong-Hyun Lee
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引用次数: 0

摘要

随着通信技术的飞速发展,人们可以开发出多种多样的数字设备。与此同时,越来越多的人开始意识到网络空间的重要性。事实上,各种数据实时存储在网上,对人们的生活产生了重大影响。尤其是被归类为非结构化数据的 "文本",在包括个人生活在内的各个领域都具有重要影响。因此,文本研究技术、方法和机构应运而生。随着 K-beauty 在全球的流行,美容行业的相关数据也得到了实时积累。在这种情况下,有必要通过分析来探讨产业发展。本研究试图利用多种大数据分析技术中的文本挖掘技术,提取与发型相关的关键词并分析高频文本。目的是了解这些文本在关键词认知方面的联系,并弄清发型设计行业的现状。预计研究结果将成为大数据研究的基础数据。此外,还希望进一步研究大数据,促进韩国美容业的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hair Beauty Keyword Derivation Analysis Using Text Mining Technique
With the rapid growth and development of communication technology, it has been possible to develop diverse digital devices. At the same time, more people have become aware of the importance of online spaces. In fact, diverse data are stored online in realtime, having a significant influence on people’s lives. In particular, ‘texts’ categorized as unstructured data have been influential in diverse fields including personal life. Therefore, text research techniques, methodologies and institutes have appeared. With the popularity of K-beauty around the world, related data in cosmetology industry have also been accumulated on a realtime basis. Under these circumstances, there is a necessity to discuss industrial development through analysis. This study attempted to extract hairstyling-related keywords and analyze top frequency texts, using text mining among diverse big data analysis techniques. The goal is to understand how such texts are connected in awareness of keywords and figure out the current situation of hairstyling industry. It is anticipated that the study results would be available as basic data for big data research. It is also expected that there would be further studies on big data for the development of Korean beauty industry.
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