@inproceedings{72ab33f8900d4a38b94720f658488204,
title = "Forecasting tourist arrivals with machine learning and internet search index",
abstract = "The queries entered into search engines register hundreds of millions of different searches by tourists, not only reflecting the trends of the searchers' preferences for travel products, but also offering a forecasting of their future travel behavior. This paper proposed a forecasting framework based on internet search index and machine learning to forecast tourist arrivals, and compared the forecasting performance of two different search engines data, Baidu and Google. The empirical results suggest that the proposed KELM models by fusing Baidu index and Google index can significantly improve the forecasting performance and outperform other benchmark models in terms of forecasting accuracy.",
keywords = "Tourism forecasting, big data analytics, composite search index, kernel extreme learning machine, search query data",
author = "Shaolong Sun and Shouyang Wang and Yunjie Wei and Xianduan Yang and Tsui, \{Kwok Leung\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 5th IEEE International Conference on Big Data, Big Data 2017 ; Conference date: 11-12-2017 Through 14-12-2017",
year = "2017",
month = jul,
day = "1",
doi = "10.1109/BigData.2017.8258439",
language = "英语",
series = "Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4165--4169",
editor = "Jian-Yun Nie and Zoran Obradovic and Toyotaro Suzumura and Rumi Ghosh and Raghunath Nambiar and Chonggang Wang and Hui Zang and Ricardo Baeza-Yates and Ricardo Baeza-Yates and Xiaohua Hu and Jeremy Kepner and Alfredo Cuzzocrea and Jian Tang and Masashi Toyoda",
booktitle = "Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017",
}