Due to the rapid development of non-face-to-face services due to the corona virus, commerce through the Internet, such as sales and reservations, is increasing very rapidly. Consumers also post reviews, suggestions, or judgments about goods or services on the website. The review data directly used by consumers provides positive feedback and nice impact to consumers, such as creating business value. Therefore, analysing review data is very important from a marketing point of view. Our research suggests a new way to find factors for customer satisfaction through review data. We applied a method to find factors for customer satisfaction by mixing and using the data mining technique, which is a big data analysis method, and the natural language processing technique, which is a language processing method, in our research. Unlike many studies on customer satisfaction that have been conducted in the past, our research has a novelty of the thesis by using various techniques. And as a result of the analysis, the results of our experiments were very accurate.
翻译:由于冠状病毒造成的非面对面服务的迅速发展,通过互联网进行的商务,例如销售和预订,正在迅速增长。消费者还张贴了网站上关于商品和服务的审查、建议或判断。消费者直接使用的审查数据为消费者提供了积极的反馈和良好的影响,例如创造商业价值。因此,分析审查数据从销售角度来说非常重要。我们的研究表明,通过审查数据找到客户满意度因素的新方式。我们采用了一种方法,通过混合和使用数据挖掘技术(这是一种大数据分析方法)和自然语言处理技术(一种语言处理方法)来寻找客户满意度的因素。与过去进行的关于客户满意度的许多研究不同,我们的研究通过使用各种技术对它进行了新颖的研究。分析的结果是非常准确的。