In recent years, multiplex network embedding has received great attention from researchers.
However, existing multiplex network embedding methods neglect structural role information …

Network embedding is a fundamental part of many network analysis tasks, including node
classification and link prediction. The existing random walk-based embedding methods aim …

Coupled propagation dynamics based on complex networks have received widespread
attention in recent years. This work reviews the research work related to coupling …

Recently, the Metaverse has received much attention, especially from large companies,
such as Meta. The social nature of the Metaverse opens new ways for immersive social …

Nowadays, many online users find the selection of information and required products
challenging due to the growing volume of data on the web. Recommender systems are …

Sentiment analysis has the potential to significantly impact several fields, such as trade,
politics, and opinion extraction. Topic modeling is an intriguing concept used in emotion …

The occurrence of diffusion on a graph is a prevalent and significant phenomenon, as
evidenced by the spread of rumors, influenza-like viruses, smart grid failures, and similar …

This article deals with finite/fixed-time cluster synchronization (FnTCS/FdTCS) issue for
directed and multiplex coupled dynamic networks (MCDNs). Finite/fixed-time …

Multi-task learning (MTL) is a joint learning paradigm to improve the generalization
performance of the tasks. At present, most of MTL methods are all based on one hypothesis …

For a state or non-state actor whose credibility is bankrupt, relying on bots to conduct non-
attributable, non-accountable, and influence/information operations (info ops) that are …