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Spatial Algorithms Syst."],"published-print":{"date-parts":[[2019,6,30]]},"abstract":"<jats:p>Understanding crowd mobility in a metropolitan area is extremely valuable for city planners and decision makers. However, crowd mobility is a relatively new area of research and has significant technical challenges: lack of large-scale fine-grained data, difficulties in large-scale trajectory processing, and issues with spatial resolution. In this article, we propose a novel approach for analyzing crowd mobility on a \u201ccity block\u201d level. We first propose algorithms to detect homes, working places, and stay regions for individual user trajectories. Next, we propose a method for analyzing commute patterns and spatial correlation at a city block level. Using mobile cellular accessing trace data collected from users in Shanghai, we discover commute patterns, spatial correlation rules, as well as a hidden structure of the city based on crowd mobility analysis. Therefore, our proposed methods contribute to our understanding of human mobility in a large metropolitan area.<\/jats:p>","DOI":"10.1145\/3323345","type":"journal-article","created":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T12:34:33Z","timestamp":1564058073000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Understanding Metropolitan Crowd Mobility via Mobile Cellular Accessing Data"],"prefix":"10.1145","volume":"5","author":[{"given":"Hancheng","family":"Cao","sequence":"first","affiliation":[{"name":"Beijing National Research Center for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jagan","family":"Sankaranarayanan","sequence":"additional","affiliation":[{"name":"University of Maryland, College Park, MD"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Feng","sequence":"additional","affiliation":[{"name":"Beijing National Research Center for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing National Research Center for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanan","family":"Samet","sequence":"additional","affiliation":[{"name":"University of Maryland, College Park, MD"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Understanding individual human mobility patterns. 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