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20112019
most citedUnsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

803 citations · 1.2k across the 20 of their papers we have counts for

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6 papers · 1 filter

physics.soc-ph2017★ 50 cited

Accurate ranking of influential spreaders in networks based on dynamically asymmetric link-impact

Ying Liu, Ming Tang, Younghae Do +1

We propose an efficient and accurate measure for ranking spreaders and identifying the influential ones in spreading processes in networks. While the edges determine the connection…

physics.soc-ph2016★ 49 cited

Social contagions on time-varying community networks

Mian-Xin Liu, Wei Wang, Ying Liu +3

Time-varying community structures widely exist in various real-world networks. However, the spreading dynamics on this kind of network has not been fully studied. To this end, we s…

physics.soc-ph2015★ 158 cited

Identify influential spreaders in complex networks, the role of neighborhood

Ying Liu, Ming Tang, Tao Zhou +1

Identifying the most influential spreaders is an important issue in controlling the spreading processes in complex networks. Centrality measures are used to rank node influence in…

physics.soc-ph2015

Improving the accuracy of the k-shell method by removing redundant links-from a perspective of spreading dynamics

Ying Liu, Ming Tang, Tao Zhou +1

Recent study shows that the accuracy of the k-shell method in determining node coreness in a spreading process is largely impacted due to the existence of core-like group, which ha…

physics.soc-ph2012★ 8 cited

Effects of Weak Ties on Epidemic Predictability in Community Networks

Panpan Shu, Ming Tang, Kai Gong +1

Weak ties play a significant role in the structures and the dynamics of community networks. Based on the susceptible-infected model in contact process, we study numerically how wea…

physics.soc-ph2012★ 24 cited

Epidemic Variability in Hierarchical Geographical Networks with Human Activity Patterns

Zhi-Dan Zhao, Ying Liu, Ming Tang

Recently, some studies have revealed that non-Poissonian statistics of human behaviors stem from the hierarchical geographical network structure. On this view, we focus on epidemic…