Development of a Tourism Information QA Service for the Task-oriented Chatbot Service

• Published in: International Journal of Advanced Culture Technology(IJACT) Vol. 12; no. 3; pp. 73 - 79
• Main Authors: 강훈철, 강명균, 좌정우
• Format: Journal Article
• Language: English
• Published: 국제문화기술진흥원 30.09.2024
• Subjects: 과학기술학; Question Answering; Smart tourism; Named Entity Recognition; Dialogue State Tracking; Trask-oriented chatbot service; Machine Reading Comprehension
• ISSN: 2288-7202; 2288-7318
• DOI: 10.17703/IJACT.2024.12.3.73

The smart tourism chatbot service provide smart tourism services to users easily and conveniently along with the smart tourism app. In this paper, the tourism information QA (Question Answering) service is proposed based on the task-oriented smart tourism chatbot system [13]. The tourism information QA service is an MRC (Machine reading comprehension)-based QA system that finds answers in context and provides them to users. The tourism information QA system consists of NER (Named Entity Recognition), DST (Dialogue State Tracking), Neo4J graph DB, and QA servers. We propose tourism information QA service uses the tourism information NER model and DST model to identify the intent of the user's question and retrieves appropriate context for the answer from the Neo4J tourism knowledgebase. The QA model finds answers from the context and provides them to users through the smart tourism app. We develop the tourism information QA model by transfer learning the bigBird model, which can process the context of 4,096 tokens, using the tourism information QA dataset.