Wikipedia in the Tourism Industry: Forecasting Demand and Modeling Usage Behavior
Abstract
Due to the economic and social impacts of tourism, both private and public sectors are interested in precisely forecasting the tourism demand volume in a timely manner. With recent advances in social networks, more people use online resources to plan their future trips. In this paper we explore the application of Wikipedia usage trends (WUTs) in tourism analysis. We propose a framework that deploys WUTs for forecasting the tourism demand of Hawaii. We also propose a data-driven approach, using WUTs, to estimate the behavior of tourists when they plan their trips.
Cite
Text
Khadivi and Ramakrishnan. "Wikipedia in the Tourism Industry: Forecasting Demand and Modeling Usage Behavior." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I2.19078Markdown
[Khadivi and Ramakrishnan. "Wikipedia in the Tourism Industry: Forecasting Demand and Modeling Usage Behavior." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/khadivi2016aaai-wikipedia/) doi:10.1609/AAAI.V30I2.19078BibTeX
@inproceedings{khadivi2016aaai-wikipedia,
title = {{Wikipedia in the Tourism Industry: Forecasting Demand and Modeling Usage Behavior}},
author = {Khadivi, Pejman and Ramakrishnan, Naren},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2016},
pages = {4016-4021},
doi = {10.1609/AAAI.V30I2.19078},
url = {https://mlanthology.org/aaai/2016/khadivi2016aaai-wikipedia/}
}