Population Location and Movement Estimation Through Cross-Domain Data Analysis
Abstract
Estimations on people movement behaviour within a country can provide valuable information to government strategic resource plannings. In this paper, we propose to utilize multi-domain statistical data to estimate people movements under the assumption that most population tend to move to areas with similar or better living conditions. We design a Multi-domain Matrix Factorization (MdMF) model to discover the underlying consistency patterns from these cross-domain data and estimate the movement trends using the proposed model. This research can provide important theoretical support to government and agencies in strategic resource planning and investments.
Cite
Text
Yang and Liu. "Population Location and Movement Estimation Through Cross-Domain Data Analysis." International Joint Conference on Artificial Intelligence, 2020. doi:10.24963/IJCAI.2020/736Markdown
[Yang and Liu. "Population Location and Movement Estimation Through Cross-Domain Data Analysis." International Joint Conference on Artificial Intelligence, 2020.](https://mlanthology.org/ijcai/2020/yang2020ijcai-population/) doi:10.24963/IJCAI.2020/736BibTeX
@inproceedings{yang2020ijcai-population,
title = {{Population Location and Movement Estimation Through Cross-Domain Data Analysis}},
author = {Yang, Xinghao and Liu, Wei},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2020},
pages = {5192-5193},
doi = {10.24963/IJCAI.2020/736},
url = {https://mlanthology.org/ijcai/2020/yang2020ijcai-population/}
}