Density-based place clustering using geo-social network data
Spatial clustering deals with the unsupervised grouping of places into clusters and finds
important applications in urban planning and marketing. Current spatial clustering models …
important applications in urban planning and marketing. Current spatial clustering models …
Fast community detection based on distance dynamics
L Chen, J Zhang, L Cai, Z Deng - Tsinghua Science and …, 2017 - ieeexplore.ieee.org
The distance dynamics model is excellent tool for uncovering the community structure of a
complex network. However, one issue that must be addressed by this model is its very long …
complex network. However, one issue that must be addressed by this model is its very long …
Analysis of associtivity and community structure in mobile social networks
W Zheng, XK Zhao, Z Kang - Procedia Computer Science, 2017 - Elsevier
Community structure detection is crucial attracted in field of study complex network. People
have find vast detection algorithmic of community structure of network. However, most of …
have find vast detection algorithmic of community structure of network. However, most of …
Modularity maximization using completely positive programming
S Yazdanparast, TC Havens - Physica A: Statistical Mechanics and its …, 2017 - Elsevier
Community detection is one of the most prominent problems of social network analysis. In
this paper, a novel method for Modularity Maximization (MM) for community detection is …
this paper, a novel method for Modularity Maximization (MM) for community detection is …
Learning rich geographical representations: Predicting colorectal cancer survival in the state of Iowa
Neural networks are capable of learning rich, nonlinear feature representations shown to be
beneficial in many predictive tasks. In this work, we use these models to explore the use of …
beneficial in many predictive tasks. In this work, we use these models to explore the use of …