AI Customer Service System with Pre-trained Language and Response Ranking Models for University Admissions
AI Customer Service System with Pre-trained Language and Response Ranking Models for University Admissions
复制标题
具有预训练语言和大学招生响应排名模型的人工智能客户服务系统
DOI：
10.1109/iri51335.2021.00062
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Sheng
中科院分区：
文献类型：
--
作者：
Min;Sheng
聊天机器人在客户服务系统领域的应用已经是不可或缺的技术。在高校招生工作中，客户服务系统是最重要的模式之一。本研究的目的是评估智能注册客户服务机器人系统的有效性，使用生成预训练-2（GPT-2）模型建立。本研究将联合收割机的客户服务场与注册场结合，建构以注册为场的客户服务系统。本研究使用OpenAI提出的GPT-2自然语言处理模型构建了一个大学招生领域的客户服务系统。利用BLEU生成评价模型，对大学招生客户服务系统生成的文本与参考文本进行相似度评价，判断该模型生成的文本的优劣。本文的研究贡献是，我们提出了一个人工智能（AI）的客户服务系统与预先训练的语言模型和大学招生的响应排名模型，并进行了用户评价建议的AI系统。
The application of chatbots in the field of customer service systems is already an indispensable technology. In the admissions of colleges and universities, the customer service system is one of the most important models. The objective of this study is to evaluate the efficacy of an intelligent enrollment customer service robot system established using the Generative Pre-Training-2 (GPT-2) model. In this study, we combine the customer service field of chat robots with the enrollment field to construct a customer service system with enrollment as the field. This study uses the GPT-2 natural language processing model proposed by OpenAI to construct a customer service system in the university admissions field. BLEU is utilized to generate an evaluation model to evaluate the similarity between the text generated by the university admissions customer service system and the reference text to determine if the generated text by this model is good or bad. The research contributions of this paper are that we proposed an artificial intelligence (AI) customer service system with a pre-trained language model and a response-ranking model for university admissions and conducted a user evaluation of the proposed AI system.