Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …

Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …

Abstract In recent times, Symmetric Nonnegative Matrix Factorization (SNMF), a derivative of
Nonnegative Matrix Factorization (NMF), has surfaced as a promising technique for graph …

The feature selection is an essential data preprocessing stage in data mining. The core
principle of feature selection seems to be to pick a subset of possible features by excluding …

The increasing growth of online social networks has drawn researchers' attention to link
prediction and has been adopted in many fields, including computer sciences, information …

The identification of protein complexes in protein-protein interaction networks is the most
fundamental and essential problem for revealing the underlying mechanism of biological …

Predicting links in complex networks has been one of the essential topics within the realm of
data mining and science discovery over the past few years. This problem remains an attempt …

The diffusion method is one of the main methods of community detection in complex
networks. In this method, the use of the concept that diffusion within the nodes that are …

As the community detection is able to facilitate the discovery of hidden information in
complex networks, it has been drawn a lot of attention recently. However, due to the growth …

Community detection in large-scale networks is one of the main challenges in social
networks analysis. Proposing a fast and accurate algorithm with low time complexity is vital …