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@article{ART002183668},
author={Parksuji and shin ji ok and 송상헌 and Chul Jeong},
title={Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine},
journal={Journal of Tourism Sciences},
issn={1226-0533},
year={2017},
volume={41},
number={1},
pages={13-27},
doi={10.17086/JTS.2017.41.1.13.27}

TY - JOUR
AU - Parksuji
AU - shin ji ok
AU - 송상헌
AU - Chul Jeong
TI - Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine
JO - Journal of Tourism Sciences
PY - 2017
VL - 41
IS - 1
PB - The Tourism Sciences Society Of Korea
SP - 13
EP - 27
SN - 1226-0533
AB - The purpose of this paper is to prove demand forecasting methods by utilizing online search engines. This study utilizes text mining based issues and Keyword analysis data derived from online search engines to predict the number of visitors that exist demanding forecasting. In terms of forecasting tourists, this study compared NAVER trend statistics to the statistics of a Tourism Information System. and, it was carried out by applying the most appropriate model to forecast demand time series data. Also, it compared existing tourist forecast statistic results of a Tourism Information System in order to forecast the result of statistical NAVER trends. As a result, we have found that when utilizing NAVER trends the forecast is for Andong tourists to continue to increase until 2018 year. However, forecasting results though the Tourist Information System showed that the number of tourists decreased. This study proposes practical implications based on these results.
KW - Text mining;Demand forecasting;On-line search engine;Big-data;Tourist information search behavior;An-Dong
DO - 10.17086/JTS.2017.41.1.13.27
ER -

Parksuji, shin ji ok, 송상헌 and Chul Jeong. (2017). Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine. Journal of Tourism Sciences, 41(1), 13-27.

Parksuji, shin ji ok, 송상헌 and Chul Jeong. 2017, "Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine", Journal of Tourism Sciences, vol.41, no.1 pp.13-27. Available from: doi:10.17086/JTS.2017.41.1.13.27

Parksuji, shin ji ok, 송상헌, Chul Jeong "Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine" Journal of Tourism Sciences 41.1 pp.13-27 (2017) : 13.

Parksuji, shin ji ok, 송상헌, Chul Jeong. Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine. 2017; 41(1), 13-27. Available from: doi:10.17086/JTS.2017.41.1.13.27

Parksuji, shin ji ok, 송상헌 and Chul Jeong. "Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine" Journal of Tourism Sciences 41, no.1 (2017) : 13-27.doi: 10.17086/JTS.2017.41.1.13.27

Parksuji; shin ji ok; 송상헌; Chul Jeong. Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine. Journal of Tourism Sciences, 41(1), 13-27. doi: 10.17086/JTS.2017.41.1.13.27

Parksuji; shin ji ok; 송상헌; Chul Jeong. Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine. Journal of Tourism Sciences. 2017; 41(1) 13-27. doi: 10.17086/JTS.2017.41.1.13.27

Parksuji, shin ji ok, 송상헌, Chul Jeong. Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine. 2017; 41(1), 13-27. Available from: doi:10.17086/JTS.2017.41.1.13.27

Parksuji, shin ji ok, 송상헌 and Chul Jeong. "Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine" Journal of Tourism Sciences 41, no.1 (2017) : 13-27.doi: 10.17086/JTS.2017.41.1.13.27