Abstract This paper improved Cuckoo Search Optimization (CSO) algorithm with a Genetic
Algorithm (GA) for community detection in complex networks. CSO algorithm has problems …

The most basic and significant issue in complex network analysis is community detection,
which is a branch of machine learning. Most current community detection approaches, only …

Clustering and classifying are overriding techniques in machine learning. Neighborhood
construction as a key step in these techniques has been extensively used for modeling local …

Many real-world social networks exist in the form of a complex network, which includes very
large scale networks with structured or unstructured data and a set of graphs. This complex …

Feature selection is a process that selects some important features from original feature set.
Many existing feature selection algorithms based on information theory concentrate on …

In light of the continuous evolution of cyber threats and the escalating frequency of
cyberattacks, cybersecurity knowledge graphs have emerged as vital tools for …

Data clustering is one of the important techniques of data mining that is responsible for
dividing N data objects into K clusters while minimizing the sum of intra-cluster distances …

Many real-world social networks such as brain graph, protein structure, food web,
transportation system, World Wide Web, online social networks exist in the form of a complex …

Community detection aims to identify topological structures and discover patterns in complex
networks, which presents an important problem of great significance. The problem can be …

The network partition is an important method for many key transport problems, eg, transport
network zoning, parallel computing of traffic assignment problem, and analysis of the …