• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.257-259
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• 2017

본 논문은 여행상품 일정의 POI정보를 기반으로 생성된 여행 스케줄러에 따라 실제 여행이 이루어지고 여행 중에 촬영된 사진과 여행자가 작성한 여행상품 리뷰 및 여행기 등의 정보를 매시업하여 여행노트를 생성하는 시스템을 구현하였다. 무엇보다 여행자가 일일이 자신의 여행 스케줄을 입력해야하는 번거로움을 없이 여행중에 편리성을 제공받을 수 있다.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.23-31
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• 2019

In this study, we collected data through online travel notes from January to December 2018 and analyzed the seasonal travel characteristics of individual visiting Chinese by utilizing social network analysis. The analysis showed that Seoul is a hub for Chinese travel to Korea and the main destinations for individual visiting Chinese are concentrated in Seoul, Busan, Jeju Island, Gyeongju and Gangneung, with wide differences in seasons. The research results can be used as basic data for the development of tourism courses for individual Chinese tourists to Korea, provision of tourism services and optimization of tourism facility layout. Future research can consider continuing to use network travel notes to study the tourist destination and the mode of transportation between tourist nodes, which can provide reference for the development of tourist market and the planning and design of tourist traffic.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.111-119
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• 2020

This study takes Chinese independent tourists to South Korea as the research object, mines the data of tourists' digital footprints from online travel notes, and analyzes the characteristics of the tourism flow of Chinese independent tourists to South Korea by using the method of quantitative statistics and social network analysis(SNA). The results show that Seoul, Jeju Island, Busan and Daegu are the important tourist destinations for Chinese independent tourists entering South Korea. In addition, Qingdao, Tianjin, Shenyang, Hong Kong, Foshan and Macao are crucial hubs for Chinese independent tourists to visit South Korea. In future studies, the number of sample data should be increased. The time span of data collection should be extended for studying the annual variation characteristics of tourism flow and the trend of tourism hot spots.