Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models
Since the problem proposed in late 2000s, microRNA–disease association (MDA)
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
Social network analysis: An overview
Social network analysis (SNA) is a core pursuit of analyzing social networks today. In
addition to the usual statistical techniques of data analysis, these networks are investigated …
addition to the usual statistical techniques of data analysis, these networks are investigated …
Stacking models for nearly optimal link prediction in complex networks
Most real-world networks are incompletely observed. Algorithms that can accurately predict
which links are missing can dramatically speed up network data collection and improve …
which links are missing can dramatically speed up network data collection and improve …
Link prediction in multiplex online social networks
Online social networks play a major role in modern societies, and they have shaped the way
social relationships evolve. Link prediction in social networks has many potential …
social relationships evolve. Link prediction in social networks has many potential …
Deep representation learning for social network analysis
Social network analysis is an important problem in data mining. A fundamental step for
analyzing social networks is to encode network data into low-dimensional representations …
analyzing social networks is to encode network data into low-dimensional representations …
[HTML][HTML] Performance optimization of criminal network hidden link prediction model with deep reinforcement learning
The scale of criminal networks (eg drug syndicates and terrorist networks) extends globally
and poses national security threat to many nations as they also tend to be technologically …
and poses national security threat to many nations as they also tend to be technologically …
Link prediction in social networks using computationally efficient topological features
Online social networking sites have become increasingly popular over the last few years. As
a result, new interdisciplinary research directions have emerged in which social network …
a result, new interdisciplinary research directions have emerged in which social network …
Modeling multi-scale data via a network of networks
Motivation Prediction of node and graph labels are prominent network science tasks. Data
analyzed in these tasks are sometimes related: entities represented by nodes in a higher …
analyzed in these tasks are sometimes related: entities represented by nodes in a higher …
Machine learning introduces new perspectives to data agency in K—12 computing education
This innovative practice full paper is grounded in the societal developments of computing in
the 2000s, which have brought the concept of information literacy and its many variants into …
the 2000s, which have brought the concept of information literacy and its many variants into …
[LLIBRE][B] Social data analytics
This book is an introduction to social data analytics along with its challenges and
opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on …
opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on …