电信业投诉分类方法及其应用研究

发布时间：2018-05-06 00:40

本文选题：文本挖掘 + 支持向量机　；参考：《中国管理科学》2015年S1期

【摘要】：科学的分类体系和准确的信息分类对于客服管理人员提高服务质量,挖掘客户潜在需求有着十分重要的意义。本文提出了一种电信业投诉信息分类划分体系和投诉文本分类的模型。该分类划分体系相比传统的分类体系更为简洁,但能更好地实现准确定位相关主题投诉信息的目标。实验证明:该分类划分体系有利于知识挖掘和问题定位,该模型分类结果的正确率在70%以上,能有效地进行投诉文本的分类。
[Abstract]:Scientific classification system and accurate information classification are of great significance for customer service managers to improve service quality and tap the potential needs of customers. In this paper, a classification system of complaint information and a model of complaint text classification are proposed. Compared with the traditional classification system, this classification system is more concise, but it can better achieve the goal of accurately locating the complaint information of related topics. The experimental results show that the classification system is beneficial to knowledge mining and problem location, and the accuracy of the classification results of the model is over 70%, and the classification of complaint texts can be effectively carried out.
【作者单位】：福州大学经济与管理学院;
【基金】：国家自然科学基金资助项目(71403055;71201033;71403054) 福建省社科基金资助项目(2014C126) 福建省软科学研究项目(2014R0057)
【分类号】：F626

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