高校信息化领域自动答疑客服系统关键技术研究

Ching-Chang Wu, Yuxi Chen, Ying Xiong, Junqing Yu
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引用次数: 1

摘要

为了提高高校信息客户服务的效率,设计并实现了一个自动答疑客户服务系统。它可以将收集到的特定领域语料库与通用语料库结合起来进行收集,训练词向量,表示词的语义,实现基于词共现和句法分析的问题相似度计算算法,实现问题匹配。为了最小化问题匹配范围,提高匹配效率,实现了基于支持向量机的问题分类模块。最后,通过实验验证了该方法的有效性和可用性。该方法具有一定的通用性。鉴于部分高校尚未建立自动答疑客服系统,本文具有重要的研究意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Key Techniques of Automatic Question-Answering Customer Service System in College Informatization Domain
To improve the efficiency of customer service for college information, an automatic question-answering customer service system was designed and implemented. It could collect the domain-specific corpus was collected in combination with the general corpus, train word vectors, represent the semantics of words, and implement the question similarity calculation algorithm based on word co-occurrence and syntactic analysis to achieve question matching. To minimize the range of question matching and thus make the matching more efficient, a question classification module based on support vector machine (SVM) was implemented. Finally, the validity and usability of the proposed method were verified by experiments. The proposed method shows a certain universality. Given that some colleges have not established their automatic question-answering customer service system, this paper is of great research significance.
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