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| Content Provider | ACM Digital Library |
|---|---|
| Author | Shibasaki, Ryosuke Song, Xuan Fan, Zipei |
| Abstract | People flow at a citywide level is in a mixed state with several basic patterns (e.g. commuting, working, commercial), and it is therefore difficult to extract useful information from such a mixture of patterns directly. In this paper, we proposed a novel tensor factorization approach to modeling city dynamics in a basic life pattern space (CitySpectral Space). To obtain the CitySpectrum, we utilized Non-negative Tensor Factorization (NTF) to decompose a people flow tensor into basic life pattern tensors, described by three bases i.e. the intensity variation among different regions, the time-of-day and the sample days. We apply our approach to a big mobile phone GPS log dataset (containing 1.6 million users) to model the fluctuation in people flow before and after the Great East Japan Earthquake from a CitySpectral perspective. In addition, our framework is extensible to a variety of auxiliary spatial-temporal data. We parametrize a people flow with a spatial distribution of the Points of Interest (POIs) to quantitatively analyze the relationship between human mobility and POI distribution. Based on the parametric people flow, we propose a spectral approach for a site-selection recommendation and people flow simulation in another similar area using POI distribution. |
| Starting Page | 213 |
| Ending Page | 223 |
| Page Count | 11 |
| File Format | PDF QT / MOV |
| ISBN | 9781450329682 |
| DOI | 10.1145/2632048.2636073 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-09-13 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Non-negative tensor factorization Human mobility |
| Content Type | Video Text |
| Resource Type | Article |
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