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 a fundamental problem in social network analysis consisting,
roughly speaking, in unsupervised dividing social actors (modeled as nodes in a social …

Attributed graph clustering is a prominent research area, catering to the increasing need for
understanding real-world systems by uncovering exhaustive meaningful latent knowledge …

Community detection has become an important research topic in machine learning due to
the proliferation of network data. However, most existing methods have been developed …

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 …

Community detection is of great help to understand the structures and functions of complex
networks. It has become one of popular research topics in the field of complex networks …

Attributed graph clustering (AGC) is an important problem in graph mining as more and
more complex data in real-world have been represented in graphs with attributed nodes …

Community detection is an important problem in network science that discovers highly
clustered groups of nodes having similar properties. Label propagation algorithm (LPA) is …

Complex networks have a large number of nodes and edges, which prevents the
understanding of network structure and the discovery of valid information. This paper …

This study investigates customers' product design requirements through online comments
from social media, and quickly translates these needs into product design specifications …