Community detection is a classic network problem with extensive applications in various
fields. Its most common method is using modularity maximization heuristics which rarely …

This paper extensively reviews the literature of community detection in complex networks
and proposes a general classification describing the main models used for this purpose …

Multilayer networks composed of intralayer edges and interlayer edges are an important
type of complex networks. Considering the heterogeneity of nodes and edges, it is …

Community detection, which involves partitioning nodes within a network, has widespread
applications across computational sciences. Modularity-based algorithms identify …

The development of statistically and biologically competent Community Detection Algorithm
(CDA) is essential for extracting hidden information from massive biological datasets. This …

Community detection, a fundamental problem in computational sciences, finds applications
in various domains. Heuristics are often employed to detect communities through …

This chapter presents how communities in networks can be detected by integrating
barycentric serialization with bottom-up segmentation. Because nodes are efficiently …

Various information systems in libraries generate a large amount of transaction data during
their operation. These data contain rich learning behavior information of learners, as well as …