认知技术模型与聊天机器人增强学术支持服务

Marilyn Choque-Díaz, Jimmy Armas-Aguirre, P. Shiguihara-Juárez
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引用次数: 5

摘要

在本文中,我们提出了一个认知技术模型来增强聊天机器人的学术支持服务。传统模型与本文模型的不同之处在于在聊天机器人中加入了客户体验模式。这可以大大改善聊天机器人和学生之间的互动。我们提出的模型还强调使用实时数据处理的最佳实践。该模型包括五个阶段:1。捕获;2. 理解自然语言;3.对话框管理;4. 反应生成的;5. 消费。我们在秘鲁应用科学大学的本科生中评估了我们的认知技术模型。初步结果显示,每个查询的预期平均响应时间减少了99.9%以上,目标人群的接受程度为80%。
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Cognitive technology model to enhanced academic support services with chatbots
In this paper, we propose a cognitive technology model to enhance academic support services with chatbots. The difference between the conventional models and the model proposed in this paper lies in adding Customer Experience patterns to the chatbot. This could substantially improve the interaction between the chatbot and the student in the institution. Our proposed model also emphasizes the use of best practices for real-time data processing. The model consists of five phases: 1. Capture; 2. Understanding Natural Language; 3. Dialog management; 4. Generated responses; 5. Consumption. We evaluate our cognitive technology model with undergraduate students at Universidad Peruana de Ciencias Aplicadas. The preliminary results showed a reduction of more than 99.9% in the average response time expected per query and an acceptance level of 80% within the target population.
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