Developing a Vietnamese Tourism Question Answering System Using Knowledge Graph and Deep Learning

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. Firstly, 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, etc. Finally, the system recommends some relating tourist attractions to users. Meanwhile, deep learning is used to solve a simple natural language answer, knowledge graph is used to infer a natural language answering list relating to entities in the question. The study experiments on a manual dataset collecting 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.