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Method of Classification of Tonal Estimations Time Series in Problems of Intellectual Analysis of Text Content

机译:色调估计时间序列分类方法文本内容的智力分析问题

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摘要

Time series of tonal estimations that occurs in the process of sentiment analysis of the flow of text messages (from messengers, social networks, etc.) can contain significant information about the dynamics of emotions of subjects that generate the message. Intellectual analysis of such time series enable to find certain patterns of emotions dynamics, for example, in responses of clients of the transport company, taxi clients, etc. In this article a method of classification of time series of tonal estimates of short text messages based on PCA is developed. Authors showed up that the process of sentiment analysis of sufficiently short time series of tonal estimates enabled to identify situations where customer feedback has a negative or positive trend. The use of such method by managers or chat-bots will increase the level of maintenance of the transport infrastructure, clients, etc.
机译:在文本消息流程(来自信使,社交网络等)的情绪分析过程中发生的调度估计的时间序列可以包含有关生成消息的受试者情绪动态的重要信息。这种时间序列的智力分析使得能够找到某些情感动态模式,例如,在本条中,在运输公司,出租车客户端等客户的响应中。基于短信消息的时间序列的时间序列分类方法在PCA开发。作者展示了感应分析的感应分析过程,其有足够短的时间序列的音调估计,以确定客户反馈具有负面或积极趋势的情况。通过管理者或聊天机器人使用这种方法将增加运输基础设施,客户等的维护水平

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