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Design Automation System for Review Analysis Affiliation for Online Educator Reliability Prediction

机译:在线教育者可靠性预测审查分析隶属关系的设计自动化系统

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In this paper, we designed a review analysis automation system to grasp the credibility of the online education matching platform. Web crawling collects and parses reviews and ratings of educators who are atypical data. We will build an emotional dictionary based on the educational field to grasp online educator credibility using collected review data and SO-PMI. We also propose a method for building large - scale learning data based on the emotion dictionary constructed. We proposed a system that provides more reliable review analysis results by measuring the accuracy of emotion dictionary by using deep learning in constructed learning data and evaluation data. Through this, we intend to help judge the credibility of educator in 020 education matching.
机译:在本文中,我们设计了审查分析自动化系统,以掌握在线教育匹配平台的可信度。 网络爬行收集和解析为非典型数据的教育工作者的评论和评级。 我们将根据教育领域建立一个情感词典,以掌握在线教育者可信度,使用收集的审核数据和所以PMI。 我们还提出了一种基于构造的情绪词典构建大规模学习数据的方法。 我们提出了一个系统,通过在构造的学习数据和评估数据中使用深度学习来测量情绪词典的准确性,提供更可靠的审查分析结果。 通过这一点,我们打算帮助判断020教育匹配的教育者的可信度。

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