Xiaogang Jin

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We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities.(More)
The analysis of human behavior is the basis of understanding many social phenomena. Based on a large database of taxi billing system, this paper provides an analysis of human mobility data in an urban area of using taxi services in Shanghai. By studying the spatial temporal data of taxi services, it shows that the distribution of running time interval is(More)
We propose a simplified model which exhibits community structure, power-law degree distribution and high clustering. Every vertex is a social one with a social identity. The preferential attachment of Barabási-Albert model is incorporated with social similarity. When a newly added vertex makes a new link, it first selects a certain group of vertices(More)
The dynamics of infectious diseases that are spread through direct contact have been proven to depend on the strength of community structure or modularity within the underlying network. It has been recently shown that weighted networks with similar modularity values may exhibit different mixing styles regarding the number of connections among communities(More)
The robustness and stability of complex cellular networks is often attributed to the redundancy of components, including genes, enzymes and pathways. Estimation of redundancy is still an open question in systems biology. Current theoretical tools to measure redundancy have various strengths and shortcomings in providing a comprehensive description of(More)