Summary of Openuas: Embeddings Of Cities in Japan with Anchor Data For Cross-city Analysis Of Area Usage Patterns, by Naoki Tamura et al.
OpenUAS: Embeddings of Cities in Japan with Anchor Data for Cross-city Analysis of Area Usage Patterns
by Naoki Tamura, Kazuyuki Shoji, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi
First submitted to arxiv on: 29 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper publicly releases OpenUAS, a large-scale dataset of area embeddings based on urban usage patterns, which can be applied to various fields such as market analysis, urban planning, transportation infrastructure, and infection prediction. The dataset captures the characteristics of each area in the city by employing an area embedding technique that utilizes location information obtained through GPS. To address the issue of not being able to embed areas from different cities and periods into the same space without sharing raw location data, the authors develop an anchoring method that establishes anchors within a shared embedding space. The paper publicly releases this anchor dataset along with area embedding datasets from several periods in eight major Japanese cities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating a big dataset that can help us understand and analyze urban areas better. It’s like creating a map of the city, but instead of just showing streets and buildings, it shows what kind of places they are (like offices or homes). This can be useful for people who want to study cities, make decisions about how to build them, or predict where diseases might spread. The dataset is special because it can take information from different cities and times and put it all together in one place. |
Keywords
* Artificial intelligence * Embedding * Embedding space
