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.
Keywords
- Data Mining: Clustering, Unsupervised Learning
- Machine Learning: Multi-instance;Multi-label;Multi-view learning
- Machine Learning: Tensor and Matrix Methods
- Machine Learning: Clustering
