基于k近邻法的在线交通服务产品情感分析

Savira Rohwinasakti, Budhi Irawan, C. Setianingsih
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引用次数: 2

摘要

2018年,东南亚地区在线交通管理每天的客户量高达800万客户/天。与其他东南亚国家相比,印度尼西亚是使用行政机构最多的国家。客户通过Instagram的评论部分,通过不同的媒体展示他们对在线运输专业合作社的管理的反应。此外,这些意见也各不相同,因此也包含了对具体行政当局的意见。以这种方式,利用k -最近邻策略制定了意见调查框架,以确定客户对给定管理的反应,履行程度,并帮助客户选择最佳管理。检验表明,该方法对客户评价的表征准确率为94.4%,在召回率和准确率方面,F1评分的结果相同,为94.4%。由此推断,从评估结果来看,所提出的计算结果对剖析意见表现良好。
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Sentiment Analysis on Online Transportation Service Products Using K-Nearest Neighbor Method
In 2018, the everyday client of online transportation administrations is up to 8 million clients/day in the Southeast Asian locale. Indonesia is the biggest country in utilizing the administrations contrasted with other Southeast Asian nations. The clients present their reactions to the administrations given by online transportation specialist co-ops through different media through the Instagram remarks segment. The responses submitted have additionally differed, so they likewise contained opinions that communicated their sentiments about specific administrations. In this manner, an opinion investigation framework was made utilizing the K-Nearest Neighbor strategy to decide clients' reactions to the administrations given, the degree of fulfillment, and assist clients with picking the best administrations. This examination shows that the proposed method can characterize client assessment with 94.4% accuracy, and for recall and precision, the F1 Score has the same result, 94.4%. This infers that from assessment results, the proposed calculation performs well to dissect opinion consequently.
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