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Chen Zhong

Researcher at King's College London

Publications -  44
Citations -  1622

Chen Zhong is an academic researcher from King's College London. The author has contributed to research in topics: Computer science & Geographic information system. The author has an hindex of 17, co-authored 38 publications receiving 1253 citations. Previous affiliations of Chen Zhong include ETH Zurich & École Normale Supérieure.

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Detecting the dynamics of urban structure through spatial network analysis

TL;DR: Singapore, even from such a short time series, is developing rapidly towards a polycentric urban form, where new subcenters and communities are emerging largely in line with the city’s master plan.
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Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data.

TL;DR: This work contributes to a deeper understanding of regularities in patterns of transit use from variations in volumes of travellers entering subway stations, establishes a generic analytical framework for comparative studies using urban mobility data, and provides key points for the management of variability by policy-makers intent on for making the travel experience more amenable.
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Measuring variability of mobility patterns from multiday smart-card data

TL;DR: A set of measuring of variability at individual and aggregated levels using multi-day smart-card data is presented, showing that a systemic framework with well-organized analytical methods is indeed, necessary for extracting variability that may change at different levels and consequently for uncovering different aspects of dynamics, namely transit, social and urban dynamics.
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Revealing centrality in the spatial structure of cities from human activity patterns

TL;DR: In this paper, the authors identify changes in the spatial structure of cities is a prerequisite for the development and validation of adequate planning strategies, but current methods of measurement are becomin...
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Inferring building functions from a probabilistic model using public transportation data

TL;DR: A method to infer urban functions at the building level using transportation data obtained from surveys and smart card systems and shows the effectiveness of applying integrated techniques to combine multi-source data in order to make insights about social activities and complex urban space.