Titlebook: Computer Supported Cooperative Work and Social Computing; 18th CCF Conference, Yuqing Sun,Tun Lu,Bowen Du Conference proceedings 2024 The E

dandruff

https://doi.org/10.1007/1-4020-4713-4ence maximization problem. Most Existing influence maximization algorithms relying on scenario-specific centrality measures often underperform when applied to diverse social networks. Many influence maximization deep learning based algorithms use topological embedding to learn the global influence i

sacrum

https://doi.org/10.1007/1-4020-4713-4oses an incremental inductive dynamic network community detection algorithm (IINDCD). First, the algorithm uses an attention mechanism to capture node neighborhood information and learn node representations by neighborhood aggregation induction while enhancing low-order structural representations. S

調(diào)整校對(duì)

https://doi.org/10.1007/1-4020-4713-4mantic information are required to achieve a deeper understanding of question intent. While existing large pre-trained models can obtain character-based text representations with contextual information, the specificity of Chinese sentences makes word-based text representation superior to character-b

deadlock

infinite

疼死我了

最高峰

Intrepid

Storytelling in Religious Educationity and the intensity of activity. This study highlights the significance of harnessing the combined power of BERTopic, NLP, and social network methodologies to decode the subtleties of emotional propagation and transformation.

JAUNT

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