论文标题
土耳其情绪分析使用机器学习方法：在线食品订单上的应用网站评论
Turkish Sentiment Analysis Using Machine Learning Methods: Application on Online Food Order Site Reviews
论文作者
论文摘要
对于当今的每个行业来说，满意度的衡量标准是许多公司的一个非常重要的因素。在这项研究中，通过使用yemek sepeti的数据以及该数据的变化，它旨在通过各种机器学习算法达到最高精度率。每种算法的精度值与所使用的各种自然语言处理方法一起计算。在计算这些准确性值时，尝试优化所使用的算法的参数。在本研究中培训的有关标记数据的模型可以用于未标记的数据，并可以使公司有一个衡量客户满意度的想法。据观察，应用的3种不同的自然语言处理方法在大多数开发模型中导致了大约5％的准确性。
Satisfaction measurement, which emerges in every sector today, is a very important factor for many companies. In this study, it is aimed to reach the highest accuracy rate with various machine learning algorithms by using the data on Yemek Sepeti and variations of this data. The accuracy values of each algorithm were calculated together with the various natural language processing methods used. While calculating these accuracy values, the parameters of the algorithms used were tried to be optimized. The models trained in this study on labeled data can be used on unlabeled data and can give companies an idea in measuring customer satisfaction. It was observed that 3 different natural language processing methods applied resulted in approximately 5% accuracy increase in most of the developed models.
