In recent years, Question Answering (QA) systems have increasingly become very popular in many sectors. This study aims to use a knowledge graph and deep learning to develop a QA system for tourism in Vietnam. First, the QA system replies to a user's question about a place in Vietnam. Then, the QA describes it in detail such as when the place was discovered, why the place's name was called like that, and so on. Finally, the system recommends some related tourist attractions to users. Meanwhile, deep learning is used to solve a simple natural language answer, and a knowledge graph is used to infer a natural language answering list related to entities in the question. The study experiments on a manual dataset collected from Vietnamese tourism websites. As a result, the QA system combining the two above approaches provides more information than other systems have done before. Besides that, the system gets 0.83 F1, 0.87 precision on the test set.

中文翻译：

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使用知识图谱和深度学习开发越南旅游问答系统

近年来，问答（QA）系统在许多领域变得越来越流行。本研究旨在使用知识图谱和深度学习来开发越南旅游业的质量保证系统。首先，QA 系统回答用户关于越南某个地方的问题。然后，QA 会详细描述它，例如这个地方是什么时候被发现的，为什么会这样称呼这个地方的名字等等。最后，系统向用户推荐一些相关的旅游景点。同时，深度学习用于解决简单的自然语言答案，知识图谱用于推断与问题中的实体相关的自然语言答案列表。对从越南旅游网站收集的手动数据集进行研究实验。因此，结合上述两种方法的 QA 系统提供的信息比其他系统以前提供的更多。除此之外，该系统在测试集上的 F1 为 0.83，精度为 0.87。