一种用于管理部门情绪估计的商业智能技术

S. Rady
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引用次数: 1

摘要

人们表达情绪是对日常情况和个人交流的反应。由于语言表达的多样性,提供对情感或情绪的准确估计是具有挑战性的。本文提出了商业领域情感估计和预测的智能技术和系统。对于管理部门来说,它很有用,因为工具可以自动分析收集的数据,并揭示员工对其组织或任何正在进行的主题的看法。这项工作的挑战在于从相对较长的文本中检测情感类别,其中作者在被要求写评论时合并句子和表达,而不是直接被要求写他们的情感程度。该方法是数据驱动的,它使用机器学习来训练分类器特征来识别情感。系统的实现和测试(基于从大型IT组织的员工评论中收集的真实数据)针对两个和五个分类等级问题。记录结果证明了该技术的有效性。
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A business intelligent technique for sentiment estimation by management sectors
People express emotions in response to everyday situation and personal communication. With diversity of language expressions, it is challenging to provide an accurate estimation of emotion or sentiment. This paper proposes intelligent technique and system for sentiment estimation and prediction in the business domain. It is useful for management sectors where tools can automatically analyze collected data and reveal employees' opinion about their organization, or any ongoing topic. The challenge in this work is to detect sentiment classes from relatively long text, where writers merge sentences and expressions when asked to write reviews, instead of being directly asked to write their sentiment degree. The approach is data-driven, which uses machine learning to train classifier features to recognize the sentiment. A system is implemented and tested (on real data collected from employee reviews at big IT organizations) towards two and five classification degrees problems. Recorded results prove efficiency of the technique.
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