DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Yoon, Yoonjin | - |
dc.contributor.advisor | 윤윤진 | - |
dc.contributor.author | Lee, Hye-Yeong | - |
dc.date.accessioned | 2023-06-21T19:30:52Z | - |
dc.date.available | 2023-06-21T19:30:52Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032219&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/307501 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 건설및환경공학과, 2023.2,[v, 69 p. :] | - |
dc.description.abstract | Urban region representation learning aims to extract valuable insights for understanding urban dynamics from diverse and intricate urban data. Since human mobility is greatly related to the socioeconomic status in a city, existing studies have comprehended urban regions through human mobility. However, it is difficult to analyze temporal variation through the previous region representations, and intrinsic evaluation is also required. Therefore, this study aims to detect temporal socioeconomic changes in urban regions via region representation learning. We modify the HUGAT model to represent region embedding for all years in one latent space. Our model outperforms baselines in predicting socioeconomic levels compared to state-of-the-art models. Furthermore, we propose a temporal similarity measure to analyze the temporal variation between 2013 and 2020 and discover regions where socioeconomic changes happen due to the inflow or outflow of a social class. This result enables efficient urban planning by monitoring each region that undergoes different changes due to social phenomena such as racial segregation or gentrification in Chicago. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Urban region representation learning▼aUrban region embedding▼aUrban heterogeneous information network▼aTemporal heterogeneous information network▼aSocioeconomic variation | - |
dc.subject | 도심 지역 표현 학습▼a도시 지역 임베딩▼a도시 이종 정보 네트워크▼a사회적 이종 정보 네트워크▼a사회경제적 변화 | - |
dc.title | Detecting temporal socioeconomic changes of regions in Chicago via urban region representation learning | - |
dc.title.alternative | 도시 지역 표현 학습을 통한 시카고의 사회 경제적 변화 감지 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :건설및환경공학과, | - |
dc.contributor.alternativeauthor | 이혜영 | - |
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